StratifiedKfold-80--20.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: Sastrawi in c:\\users\\asus\\anaconda3\\lib\\site-packages (1.0.1)\n"
     ]
    }
   ],
   "source": [
    "!pip install Sastrawi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\ASUS\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re\n",
    "from collections import Counter\n",
    "import pickle\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import nltk\n",
    "nltk.download('punkt')\n",
    "from Sastrawi.Stemmer.StemmerFactory import StemmerFactory\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.model_selection import cross_validate\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import PowerTransformer, RobustScaler\n",
    "import seaborn as sns\n",
    "from sklearn.metrics import accuracy_score,confusion_matrix, classification_report\n",
    "from Sastrawi.StopWordRemover.StopWordRemoverFactory import StopWordRemoverFactory\n",
    "from nltk.tokenize import word_tokenize\n",
    "\n",
    "\n",
    "pd.set_option('max_columns', 1000)\n",
    "pd.set_option('max_rows', 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = ['Kode Berita','Judul Berita','Isi Berita', 'Kategori']\n",
    "\n",
    "# Hoax data\n",
    "hoax = pd.read_excel('C:/Users/ASUS/Downloads/Data hoax (1)_100.xlsx', usecols=cols)\n",
    "\n",
    "# Non Hoax Data\n",
    "nonhoax = pd.read_excel('C:/Users/ASUS/Downloads/Data 4 sumber.xlsx', usecols=cols)\n",
    "\n",
    "# Concat Data and Shuffle \n",
    "df = pd.concat([hoax, nonhoax], ignore_index=True)\n",
    "df = df.sample(frac=1).reset_index(drop=True)\n",
    "df.to_csv('C:/Users/ASUS/Downloads/Data 80-20.csv', index_label=None, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = ['Kode Berita','Judul Berita','Isi Berita', 'Kategori']\n",
    "df = pd.read_csv('C:/Users/ASUS/Downloads/Data 80-20.csv', usecols=cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Kode Berita</th>\n",
       "      <th>Judul Berita</th>\n",
       "      <th>Isi Berita</th>\n",
       "      <th>Kategori</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Nhoax_28</td>\n",
       "      <td>Kasus Baru Corona Eropa Berlipat Ganda 10 Hari...</td>\n",
       "      <td>Kasus virus Corona COVID-19 Eropa naik dua kal...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Nhoax_73</td>\n",
       "      <td>Tanda dan Gejala Kanker Serviks</td>\n",
       "      <td>Kanker serviks adalah jenis kanker yang terjad...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Nhoax_5</td>\n",
       "      <td>5 Masalah yang Muncul Akibat Tidur Kurang dari...</td>\n",
       "      <td>Berapa jam Anda tertidur setiap malam? Jika ku...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hoax_3</td>\n",
       "      <td>Pengecilan Otak Pada Anak-Anak Karena Radiasi...</td>\n",
       "      <td>Bgi yg punya anak putra putrinya harus di awas...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hoax_48</td>\n",
       "      <td>MENGETAHUI KANDUNGAN PASTA GIGI DARI KODE WARNA</td>\n",
       "      <td>Coba cek kode warna register pd pasta gigi and...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Hoax_65</td>\n",
       "      <td>Cara Cepat Cek Jantung Dengan Air dan Es Batu</td>\n",
       "      <td>INGIN MENGETAHUI BAGAIMANA KESEHATAN JANTUNG A...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Hoax_83</td>\n",
       "      <td>Nasi Padang Menjadi Sumber Penularan Covid-19</td>\n",
       "      <td>Nasi Padang sumber penularan virus Covid-19 . ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nhoax_96</td>\n",
       "      <td>Memahami Penyebab dan Gejala Alergi Penisilin</td>\n",
       "      <td>Menurut Mayo Clinic, tanda dan gejala alergi p...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Hoax_7</td>\n",
       "      <td>Dokter Italia Sengaja Membunuh Pasien Virus C...</td>\n",
       "      <td>Seorang dokter Italia di pusat perjuangan nega...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Hoax_19</td>\n",
       "      <td>Menkes Mengatakan Masih Ada 3.500 Dokter \"Cada...</td>\n",
       "      <td>Pernyataan Menteri Kesehatan, Terawan Agus Put...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Kode Berita                                       Judul Berita  \\\n",
       "0    Nhoax_28  Kasus Baru Corona Eropa Berlipat Ganda 10 Hari...   \n",
       "1    Nhoax_73                    Tanda dan Gejala Kanker Serviks   \n",
       "2     Nhoax_5  5 Masalah yang Muncul Akibat Tidur Kurang dari...   \n",
       "3      Hoax_3   Pengecilan Otak Pada Anak-Anak Karena Radiasi...   \n",
       "4     Hoax_48    MENGETAHUI KANDUNGAN PASTA GIGI DARI KODE WARNA   \n",
       "5     Hoax_65      Cara Cepat Cek Jantung Dengan Air dan Es Batu   \n",
       "6     Hoax_83      Nasi Padang Menjadi Sumber Penularan Covid-19   \n",
       "7    Nhoax_96      Memahami Penyebab dan Gejala Alergi Penisilin   \n",
       "8      Hoax_7   Dokter Italia Sengaja Membunuh Pasien Virus C...   \n",
       "9     Hoax_19  Menkes Mengatakan Masih Ada 3.500 Dokter \"Cada...   \n",
       "\n",
       "                                          Isi Berita  Kategori  \n",
       "0  Kasus virus Corona COVID-19 Eropa naik dua kal...         0  \n",
       "1  Kanker serviks adalah jenis kanker yang terjad...         0  \n",
       "2  Berapa jam Anda tertidur setiap malam? Jika ku...         0  \n",
       "3  Bgi yg punya anak putra putrinya harus di awas...         1  \n",
       "4  Coba cek kode warna register pd pasta gigi and...         1  \n",
       "5  INGIN MENGETAHUI BAGAIMANA KESEHATAN JANTUNG A...         1  \n",
       "6  Nasi Padang sumber penularan virus Covid-19 . ...         1  \n",
       "7  Menurut Mayo Clinic, tanda dan gejala alergi p...         0  \n",
       "8  Seorang dokter Italia di pusat perjuangan nega...         1  \n",
       "9  Pernyataan Menteri Kesehatan, Terawan Agus Put...         1  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    " def cf_cl_tn(berita):\n",
    "    # lowercase\n",
    "    normal_br = str(berita).lower()\n",
    "    # hapus @username\n",
    "    normal_br = re.sub(r'@[^\\s]+', '', normal_br)\n",
    "    # hapus hashtag\n",
    "    normal_br = re.sub(r'#[^\\s]+', '', normal_br)\n",
    "    # hapus tanda baca\n",
    "    normal_br = re.sub(r'[^\\w\\s]', '', normal_br) \n",
    "    # hapus angka\n",
    "    normal_br = re.sub(r'\\d+', '', normal_br)\n",
    "    # remove spasi berlebih\n",
    "    normal_br = re.sub(r'\\s+', ' ', normal_br)\n",
    "    # trim depan belakang\n",
    "    normal_br = normal_br.strip()\n",
    "    #tokenizer\n",
    "    normal_br = ''.join([i for i in normal_br if ord(i) < 5000])\n",
    "    # regex huruf yang berulang seperti haiiii (untuk fitur unigram)\n",
    "    normal_regex = re.compile(r\"(.)\\1{1,}\")\n",
    "    # buang huruf yang berulang\n",
    "    normal_br = normal_regex.sub(r\"\\1\\1\", normal_br)\n",
    "    return normal_br"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Isi Berita']=df['Isi Berita'].apply(cf_cl_tn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stopword_pp(berita):\n",
    "    factory = StopWordRemoverFactory()\n",
    "    stopword = factory.create_stop_word_remover()\n",
    "    return stopword.remove(berita)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['yang', 'untuk', 'pada', 'ke', 'para', 'namun', 'menurut', 'antara', 'dia', 'dua', 'ia', 'seperti', 'jika', 'jika', 'sehingga', 'kembali', 'dan', 'tidak', 'ini', 'karena', 'kepada', 'oleh', 'saat', 'harus', 'sementara', 'setelah', 'belum', 'kami', 'sekitar', 'bagi', 'serta', 'di', 'dari', 'telah', 'sebagai', 'masih', 'hal', 'ketika', 'adalah', 'itu', 'dalam', 'bisa', 'bahwa', 'atau', 'hanya', 'kita', 'dengan', 'akan', 'juga', 'ada', 'mereka', 'sudah', 'saya', 'terhadap', 'secara', 'agar', 'lain', 'anda', 'begitu', 'mengapa', 'kenapa', 'yaitu', 'yakni', 'daripada', 'itulah', 'lagi', 'maka', 'tentang', 'demi', 'dimana', 'kemana', 'pula', 'sambil', 'sebelum', 'sesudah', 'supaya', 'guna', 'kah', 'pun', 'sampai', 'sedangkan', 'selagi', 'sementara', 'tetapi', 'apakah', 'kecuali', 'sebab', 'selain', 'seolah', 'seraya', 'seterusnya', 'tanpa', 'agak', 'boleh', 'dapat', 'dsb', 'dst', 'dll', 'dahulu', 'dulunya', 'anu', 'demikian', 'tapi', 'ingin', 'juga', 'nggak', 'mari', 'nanti', 'melainkan', 'oh', 'ok', 'seharusnya', 'sebetulnya', 'setiap', 'setidaknya', 'sesuatu', 'pasti', 'saja', 'toh', 'ya', 'walau', 'tolong', 'tentu', 'amat', 'apalagi', 'bagaimanapun']\n"
     ]
    }
   ],
   "source": [
    "factory = StopWordRemoverFactory()\n",
    "stopwords = factory.get_stop_words()\n",
    "print(stopwords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Isi Berita']=df['Isi Berita'].apply(stopword_pp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stemming_pp(berita):\n",
    "    factory = StemmerFactory()\n",
    "    stemmer = factory.create_stemmer()\n",
    "    return stemmer.stem(berita)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Isi Berita']=df['Isi Berita'].apply(stemming_pp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stopword_normalisasi_tambahan(berita):\n",
    "    stopwords = pd.read_csv('C:/Users/ASUS/Downloads/stopword.csv', header=None)\n",
    "\n",
    "    df_kamus_singkatan = pd.read_csv('C:/Users/ASUS/Downloads/kamus_singkatan - kamus_singkatan (1).csv')\n",
    "    df_kamus_alay = pd.read_csv('C:/Users/ASUS/Documents/klasifikasi hoax/colloquial-indonesian-lexicon.csv')\n",
    "\n",
    "    token = nltk.word_tokenize(berita)\n",
    "    token_new = []\n",
    "    for k in token:\n",
    "        if k in df_kamus_singkatan['singkatan'].values:\n",
    "            k = df_kamus_singkatan.loc[df_kamus_singkatan['singkatan']\n",
    "                                       == k, 'asli'].values[0]\n",
    "        if k in df_kamus_alay['slang'].values:\n",
    "            k = df_kamus_alay.loc[df_kamus_alay['slang']\n",
    "                                  == k, 'formal'].values[0]\n",
    "        if k not in stopwords[0].values:\n",
    "            token_new.append(k)\n",
    "\n",
    "    str_clean = ' '.join(token_new)\n",
    "    return str_clean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Isi Berita']=df['Isi Berita'].apply(stopword_normalisasi_tambahan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      kasus virus covid covid eropa naik kali lipat ...\n",
       "1      kanker serviks jenis kanker jadi selsel leher ...\n",
       "2      berapa jam tidur malam kurang tujuh jam perlu ...\n",
       "3      punya anak putra putri awasin suka main hpini ...\n",
       "4      coba cek kode warna register pasta gigi letak ...\n",
       "5      tahu bagaimana sehat jantung tes sederhana det...\n",
       "6      nasi padang sumber tular virus covid coba baya...\n",
       "7      mayo clinic tanda gejala alergi penisilin seri...\n",
       "8      orang dokter italia pusat juang negara lawan v...\n",
       "9      nyata menteri sehat awan agus putranto soal ba...\n",
       "10     pandemi virus covid china tengah hadap jadi lu...\n",
       "11     paruparu basah rupa istilah rujuk sakit pneumo...\n",
       "12     usaha obat bas swiss novartis lampu hijau bada...\n",
       "13     noorsy video kata thermo gun laser resiko otak...\n",
       "14     anosmia bukan gejala khas virus memang dulu pe...\n",
       "15     laku imunisasi anak rupa penting meski khawati...\n",
       "16     paham betul teori generatio spontanea runtuh s...\n",
       "17     anggur murah giur info wa saudara tahu info ik...\n",
       "18     barangkali alami momen antri lama pandemi viru...\n",
       "19     dokter saran indonesia kan daun sirih mana ker...\n",
       "20     jakarta cnn indonesia center for disease and p...\n",
       "21     ramai media sosial buah postingan upa foto bel...\n",
       "22     pernah habis kantung makan sadar lalu rasa mak...\n",
       "23     rasa tekan pandemi virus covid lebih tenaga me...\n",
       "24     wanita konsumsi cukup vitamin sih manfaat ikut...\n",
       "25     studi kohort retrospektif ujung rilis jurnal l...\n",
       "26     banyak warga korea selatan tinggal usai jalan ...\n",
       "27     stoian alexov ahli pathologi eropa sebut who o...\n",
       "28     orang ng mem l golong n r h o terb l ng leb h ...\n",
       "29     kanker bukan sakit bisnis miliar dolar artikel...\n",
       "30     sukarelawan uji klinis vaksin covid astrazenec...\n",
       "31     spanyol jadi negara pertama eropa barat catat ...\n",
       "32     perhati gemar makan laut bila menampak perut i...\n",
       "33     juta produksi rokok papar covid edar luas masy...\n",
       "34     bantu kasih tahu saudara kena covid obat beri ...\n",
       "35     infeksi ginjal sakit timbul komplikasi serius ...\n",
       "36     zinc rupa nutrisi main peran penting sehat sel...\n",
       "37     perhati jangan cek darah sebut gratis tempat a...\n",
       "38     lumpuh badan akibat sumbat maupun darah menamp...\n",
       "39     inggris jadi negara pertama infeksi rawan laku...\n",
       "40     nyala ac pertama masuk mobil jendela tutup kan...\n",
       "41     obat pil kecil sterilisasi obat sekarang pakai...\n",
       "42     vaksin autis buat pasang muda om tante punya k...\n",
       "43     hubung himbauan perintah daerah terima tamu lu...\n",
       "44     masa pandemi multivitamin jadi pegang banyak o...\n",
       "45     info penting hati hati lihat langsung korban i...\n",
       "46     rumput fatimah satu tanam herbal kenal turun t...\n",
       "47     kabar baik nih studi baru temu tidur siang san...\n",
       "48     hubung sebut lapor tutup kyku production sablo...\n",
       "49     masjid tutup turki ancam virus covid tutup mas...\n",
       "50     tingkat kasus masyarakat jadi mudah percaya be...\n",
       "51     teman kelas keponakan lakilaki lulus gelar mas...\n",
       "52     mana ucap bela sungkawa presiden team medis gu...\n",
       "53     tuberkulosis tbc tulang sakit infeksi bakteri ...\n",
       "54     kabar gembira berita super obat virus sih temu...\n",
       "55     apd baru datang china angkut pesawat tni itute...\n",
       "56     sakit batu empedu mungkin asing telinga batu e...\n",
       "57     tangan cepat tepat diabetes akibat komplikas s...\n",
       "58     pemberitahuan menteri sehat publik virus covid...\n",
       "59     google mudah orang awat medis virtual perlu ti...\n",
       "60     gugus tugas covid identifikasi jumlah kelompok...\n",
       "61     pankreatitis adang pankreas pankreas kelenjar ...\n",
       "62     narasi takut lintah kangkung bunuh kangkung tn...\n",
       "63     pandemi covid infeksi lebih juta duduk bumi il...\n",
       "64     racun nasi keluar nasi rice cooker kalau matan...\n",
       "65     acehsatucom banda aceh beberapa bulan akhir ma...\n",
       "66     mungkin bagan besar tahu parasetamol obat turu...\n",
       "67     post video who nyata covid lebih takut sakit f...\n",
       "68     ayah bunda hati beri minum instan buah hati mi...\n",
       "69     vaksinasi jadi salah satu upaya akhir pandemi ...\n",
       "70     meski virus covid covid tewas lebih juta orang...\n",
       "71     komorbid sakit mati anak infeksi covid beda or...\n",
       "72     dengar saddam hussein temu tahun kabinet beri ...\n",
       "73     jumlah sintas covid nyata penting disiplin ter...\n",
       "74     diberitahukan seluruh masyarakat kab bekas mul...\n",
       "75     hubung bangun diabetes covid selesai debat jum...\n",
       "76     lembaga peduli sosial makassar lpsm berita gem...\n",
       "77     ketat protokol sehat nikmat tonton bioskop mul...\n",
       "78     pasang suamiistri konsumsi pil kb cara efektif...\n",
       "79     iring tambah jumlah pasien positif covid indon...\n",
       "80     faktor genetik gaya hidup jadi faktor utama di...\n",
       "81     menko ekonomi airlangga hartarto ungkap bijak ...\n",
       "82     pakai masker kini jadi wajib tengah pandemi vi...\n",
       "83     norovirus heboh china barubaru nyata pernah te...\n",
       "84     itly kendali virus orangorang italia ucap sela...\n",
       "85     gejala covid paling umum jadi demam batuk sesa...\n",
       "86     tegur resmi layang presiden hari minggu maret ...\n",
       "87     temu benjol payudara jangan buruburu panik tak...\n",
       "88     achmad yurianto tak jabat direktur jenderal ce...\n",
       "89     bila masak kangkung harap belah batang beberap...\n",
       "90     salah satu rawan uji klinis vaksin covid astra...\n",
       "91     otoritas china sebut total kapasitas produksi ...\n",
       "92     cegah sakit lalu imunisasi nilai jumlah pihak ...\n",
       "93     covid indonesia catat kasus baru covid lebih r...\n",
       "94     artikel now news nyata covid temu tisu toilet ...\n",
       "95     hipertensi kenal sakit darah tinggi bagai besa...\n",
       "96     tips redam convid uap air panas pakarpakar cin...\n",
       "97     nanas mungkin buah mudah temu indonesia harga ...\n",
       "98     mulai besok weekend jangan keluar rumah cari m...\n",
       "99     mulai besok jangan keluar rumah cari makan apa...\n",
       "100    covid virus bohongbukan virus bakterisemua tah...\n",
       "101    juru bicara perintah tangan covid achmad yuria...\n",
       "102    tengah pandemi covid boyolali jibaku lawan kas...\n",
       "103    menteri sehat republik indonesia awan agus put...\n",
       "104    suami bcl kata tinggal serang jantung usia tah...\n",
       "105    umur tahun buluh mata pecah banyak main hptabl...\n",
       "106    direktur sehat gizi masyarakat menteri ppnbapp...\n",
       "107    beberapa orang sedang obrol bahasa asing rekam...\n",
       "108    dokter stephen mak rawat pasien kanker stadium...\n",
       "109    izin infokanizin info yth bapakibu mohon ijin ...\n",
       "110    waspada umat islam semua vaksin mau program pe...\n",
       "111    apa sih virus covid covid virus bukan jenis ja...\n",
       "112    assalamuallaikum selamat sore malam adik syifa...\n",
       "113    manfaat mindfulness sehat fisik mental lama ja...\n",
       "114    hidup diabetes buat orang sulit kontrol kadar ...\n",
       "115    biasa rokok anggap reda sakit tubuh sayang ang...\n",
       "116    bocah kena ganggu jiwa terlalu banyak ikut les...\n",
       "117    virus covid sakit demam darah dengeu dbd tenga...\n",
       "118    istri presiden amerika serikat donald trump me...\n",
       "119    mulai hari rscm mulai praktik sedot plug sumba...\n",
       "120    sekarang bpjs pbb ngelink data samsat arti war...\n",
       "121    lansir mayo clinic jenis sakit kepala olahraga...\n",
       "122    kostokondritis bengkak tulang rawan tempel tul...\n",
       "123    pneumonia infeksi kuman buat kantong udara par...\n",
       "124    wilayah surakarta kena rs penuh kondisi anak d...\n",
       "125    perintah tengah gencar tambah fasilitas sehat ...\n",
       "126    perhati keluarga sangat bantu masa awat pasien...\n",
       "127    jangan beli sardin buat baru tadi kawan beli m...\n",
       "128    ginjal begadang maag dingin paru asap rokok ha...\n",
       "129    dar ingat buat ibu khusus punya suamidi anjur ...\n",
       "130    sebar virus covid covid makin hantu masyarakat...\n",
       "131    studi ungkap daftar prosedur medis timbul risi...\n",
       "132    minum air posisi duduk lebih sehat minum air d...\n",
       "133    spesialis obstetri ginekologi rs siloam kebon ...\n",
       "134    tanggal oktober rupa ingat hari menopause duni...\n",
       "135    rs gatot subroto jakarta mulai obat tumor gana...\n",
       "136    pusat kendali cegah sakit cdc kini baru pedoma...\n",
       "137    umum nyata ruang rawat inap bpjs sehat pindah ...\n",
       "138    hingga kini diet terus jadi tren gaya hidup ma...\n",
       "139    pernakah bangun tidur malam waktu tak mejam ma...\n",
       "140    terang foto mayat mayat orang cina gelimpang j...\n",
       "141    warga negara indonesia waspada serang virus co...\n",
       "142    makassar gosulselcom akhirakhir muncul buah vi...\n",
       "143    wuhan cina jadi virus covid rakyat bondong mes...\n",
       "144    pusat kendali sebar sakit as ikut halhal perlu...\n",
       "145    apa merek jenis vaksin efek samping jadi norma...\n",
       "146    lansir laman new york post beberapa tokoh kena...\n",
       "147    limeng yan dokter china spesial virologi imuno...\n",
       "148    lidah asa gatal makan nanas pengaruh kandung e...\n",
       "149    hipertensi esensial jenis tekan darah tinggi i...\n",
       "150    satu info sehat penting orang awam masalah ken...\n",
       "151    indonesia geger temu kasus virus covid baru ja...\n",
       "152    sariawan mungkin dengar sakit biasa tular fakt...\n",
       "153    orang dokter spesialis sakit rumah sakit phoen...\n",
       "154    virus covid pandang bulu serang siapa masuk an...\n",
       "155    salah satu diri microsoft bill gates luncur ka...\n",
       "156    menteri sehat awan agus putranto somasi organi...\n",
       "157    hias emas bayi segi analisis medis ahli beri s...\n",
       "158    jelang akhir bulan oktober khawatir libur panj...\n",
       "159    beri vaksin kanker serviks hpv anakanak usia s...\n",
       "160    epidemi influenza rebak banyak tempat dunia or...\n",
       "161    hingga vaksin obat pasien virus covid covid te...\n",
       "162    jantung berdebardebar memang jadi kapan normal...\n",
       "163    hari singapura sungguh tak pernah jadi warga s...\n",
       "164    seledri obat cuci ginjal seledri memang milik ...\n",
       "165    imunisasi vaksinasi seringkali buat banyak ora...\n",
       "166    apabila awas tekan darah kadar kolesterol tubu...\n",
       "167    cara aplikasi nya cukup mudah sih ketiak kerin...\n",
       "168    tisu basah kini jadi salah satu barang masyara...\n",
       "169    italia rakyat buang duit jalan harta bila viru...\n",
       "170    hati hati paracetamol datang tulis p paracetam...\n",
       "171    perlu cermat runing teks buah tv ustadz jabar ...\n",
       "172    foto presiden jokowi pegang gagang bambu makan...\n",
       "173    hand sanitizer sembarang nyata timbul masalah ...\n",
       "174    potong kanker keluar tubuh pasien nyata kanker...\n",
       "175    gupta kata mati kanker ceroboh langkah pertama...\n",
       "176    juta orang masyarakat cina peluk agama islam s...\n",
       "177    penting rokok lawan covid baca selesai mengunn...\n",
       "178    makan makan kedelai tahu tingkat risiko hilang...\n",
       "179    tenaga medis sampang jawa timur sengaja papar ...\n",
       "180    biasa rusak otak besar lewat sarap tidur larut...\n",
       "181    sen habib jafar bin muhammad bin hamid taruh b...\n",
       "182    masker kain filter hepa anggap lebih efektif m...\n",
       "183    covid indonesia terus tingkat hari lebih ribu ...\n",
       "184    kasus covid eropa makin ganas salah satu negar...\n",
       "185    imigran cn sengaja bawa virus sunti anti bodi ...\n",
       "186    infeksi norovirus buat rasa derita satu hari p...\n",
       "187    anoreksia nervosa ganggu makan serius mana ora...\n",
       "188    orang warga brasil jadi rawan uji klinis vaksi...\n",
       "189    influenza flu sakit hampir semua orang mungkin...\n",
       "190    kolesterol jenis zat lilin temu darah sel tubu...\n",
       "191    obat dbd temu prof aa mattjik mantan rektor ip...\n",
       "192    tampak ingat hari cuci tangan dunia global han...\n",
       "193    hipotiroid kongenital kondisi kurang hormon ti...\n",
       "194    musim hujan buat jumlah wilayah indonesia rawa...\n",
       "195    air nanas panas sebar sebar profesor khairul h...\n",
       "196    juru bicara satu tugas tangan covid reisa brot...\n",
       "197    tahu jantung paling pantang apa mungkin tahu b...\n",
       "198    produksi bh diexport negara arab mungkin indon...\n",
       "199    orang ibu rumah tangga nama nunki herwanti sem...\n",
       "Name: Isi Berita, dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Isi Berita']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature Section TF-IDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------- TF-IDF on Isi Berita -------\n",
      "TF-IDF  <class 'numpy.ndarray'> (200, 2542)\n"
     ]
    }
   ],
   "source": [
    "max_features = 5000\n",
    "\n",
    "print (\"------- TF-IDF on Isi Berita -------\")\n",
    "\n",
    "tf_idf = TfidfVectorizer(max_features=max_features, binary=True)\n",
    "tfidf_mat = tf_idf.fit_transform(df['Isi Berita']).toarray()\n",
    "\n",
    "print(\"TF-IDF \", type(tfidf_mat), tfidf_mat.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Kata</th>\n",
       "      <th>TF-IDF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>covid</td>\n",
       "      <td>6.325811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1597</th>\n",
       "      <td>orang</td>\n",
       "      <td>5.356825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2484</th>\n",
       "      <td>virus</td>\n",
       "      <td>5.355983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>911</th>\n",
       "      <td>jadi</td>\n",
       "      <td>5.283681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>sebut</td>\n",
       "      <td>4.811156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>sehat</td>\n",
       "      <td>4.634741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958</th>\n",
       "      <td>sakit</td>\n",
       "      <td>4.532380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1253</th>\n",
       "      <td>lebih</td>\n",
       "      <td>4.116984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>banyak</td>\n",
       "      <td>4.040200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>765</th>\n",
       "      <td>hari</td>\n",
       "      <td>3.756030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Kata    TF-IDF\n",
       "444    covid  6.325811\n",
       "1597   orang  5.356825\n",
       "2484   virus  5.355983\n",
       "911     jadi  5.283681\n",
       "2010   sebut  4.811156\n",
       "2024   sehat  4.634741\n",
       "1958   sakit  4.532380\n",
       "1253   lebih  4.116984\n",
       "193   banyak  4.040200\n",
       "765     hari  3.756030"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "terms = tf_idf.get_feature_names()\n",
    "\n",
    "# Menjumlah nilai tf-idf dr setiap kata - antar dokumen\n",
    "sums = tfidf_mat.sum(axis=0)\n",
    "\n",
    "# menghubungkan setiap kata pada perhitungan jumlah tf-idf\n",
    "data = []\n",
    "for col, term in enumerate(terms):\n",
    "    data.append((term, sums[col] ))\n",
    "\n",
    "ranking = pd.DataFrame(data, columns=['Kata','TF-IDF'])\n",
    "ranking = ranking.sort_values('TF-IDF', ascending=False)\n",
    "\n",
    "ranking.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modelling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "label = df['Kategori'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = pd.DataFrame(tfidf_mat)\n",
    "y = df.Kategori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data latih:  (160, 2542)\n",
      "Data Uji:  (40, 2542)\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, stratify=y, random_state=42)\n",
    "print('Data latih: ',np.shape(X_train))\n",
    "print('Data Uji: ',np.shape(X_test)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "def num_pipe(impute=None, transform='yeo-johnson', scaling='minmax'):\n",
    "    if impute is None:\n",
    "        steps = []\n",
    "    if transform is not None:\n",
    "        steps.append(('transformer', PowerTransformer(transform)))\n",
    "    if scaling == 'minmax':\n",
    "        steps.append(('scaler', MinMaxScaler()))\n",
    "    return Pipeline(steps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "preprocessor = ColumnTransformer([\n",
    "    ('numeric', num_pipe(scaling='minmax', transform='yeo-johnson'), X.columns)\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import StratifiedKFold\n",
    "cv_method = StratifiedKFold(n_splits=10, random_state=999)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "params_mnb = {'mnb__alpha': np.logspace(0,-9, num=10), 'mnb__fit_prior' : [True, False]}\n",
    "params_nb = {'nb__var_smoothing' : np.logspace(0,-9, num=10)}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Naive Bayes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 10 folds for each of 10 candidates, totalling 100 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 8 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done  34 tasks      | elapsed:  2.3min\n",
      "[Parallel(n_jobs=-1)]: Done 100 out of 100 | elapsed:  6.0min finished\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'nb__var_smoothing': 1.0}\n",
      "1.0 0.85625 0.825\n"
     ]
    }
   ],
   "source": [
    "pipeline = Pipeline([\n",
    "    ('prep', preprocessor),\n",
    "    ('nb', GaussianNB())\n",
    "])\n",
    "\n",
    "model_nb = GridSearchCV(pipeline, params_nb, cv=cv_method, n_jobs=-1, verbose=1)\n",
    "model_nb.fit(X_train, y_train)\n",
    "\n",
    "print(model_nb.best_params_)\n",
    "print(model_nb.score(X_train, y_train), model_nb.best_score_, model_nb.score(X_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_nb__var_smoothing</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>split3_test_score</th>\n",
       "      <th>split4_test_score</th>\n",
       "      <th>split5_test_score</th>\n",
       "      <th>split6_test_score</th>\n",
       "      <th>split7_test_score</th>\n",
       "      <th>split8_test_score</th>\n",
       "      <th>split9_test_score</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>26.041994</td>\n",
       "      <td>1.104018</td>\n",
       "      <td>0.531691</td>\n",
       "      <td>0.091662</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'nb__var_smoothing': 1.0}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.85625</td>\n",
       "      <td>0.079304</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25.880241</td>\n",
       "      <td>1.930201</td>\n",
       "      <td>0.545855</td>\n",
       "      <td>0.081647</td>\n",
       "      <td>0.1</td>\n",
       "      <td>{'nb__var_smoothing': 0.1}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.75000</td>\n",
       "      <td>0.073951</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26.316367</td>\n",
       "      <td>3.196692</td>\n",
       "      <td>0.554719</td>\n",
       "      <td>0.095703</td>\n",
       "      <td>0.01</td>\n",
       "      <td>{'nb__var_smoothing': 0.01}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.73125</td>\n",
       "      <td>0.068750</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25.999896</td>\n",
       "      <td>2.011534</td>\n",
       "      <td>0.542151</td>\n",
       "      <td>0.086011</td>\n",
       "      <td>0.001</td>\n",
       "      <td>{'nb__var_smoothing': 0.001}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.71250</td>\n",
       "      <td>0.063738</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25.673555</td>\n",
       "      <td>2.806531</td>\n",
       "      <td>0.514621</td>\n",
       "      <td>0.062081</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>{'nb__var_smoothing': 0.0001}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.71250</td>\n",
       "      <td>0.063738</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>26.237564</td>\n",
       "      <td>2.271084</td>\n",
       "      <td>0.483054</td>\n",
       "      <td>0.067915</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>{'nb__var_smoothing': 1e-05}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.71250</td>\n",
       "      <td>0.063738</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>26.371504</td>\n",
       "      <td>2.703069</td>\n",
       "      <td>0.547611</td>\n",
       "      <td>0.091958</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>{'nb__var_smoothing': 1e-06}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.71875</td>\n",
       "      <td>0.064043</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>26.106466</td>\n",
       "      <td>2.783630</td>\n",
       "      <td>0.549474</td>\n",
       "      <td>0.082592</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'nb__var_smoothing': 1e-07}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.71875</td>\n",
       "      <td>0.064043</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>26.540851</td>\n",
       "      <td>2.606046</td>\n",
       "      <td>0.546757</td>\n",
       "      <td>0.077959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'nb__var_smoothing': 1e-08}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.71250</td>\n",
       "      <td>0.063738</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>25.127939</td>\n",
       "      <td>0.922511</td>\n",
       "      <td>0.481404</td>\n",
       "      <td>0.083250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'nb__var_smoothing': 1e-09}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.71250</td>\n",
       "      <td>0.063738</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
       "0      26.041994      1.104018         0.531691        0.091662   \n",
       "1      25.880241      1.930201         0.545855        0.081647   \n",
       "2      26.316367      3.196692         0.554719        0.095703   \n",
       "3      25.999896      2.011534         0.542151        0.086011   \n",
       "4      25.673555      2.806531         0.514621        0.062081   \n",
       "5      26.237564      2.271084         0.483054        0.067915   \n",
       "6      26.371504      2.703069         0.547611        0.091958   \n",
       "7      26.106466      2.783630         0.549474        0.082592   \n",
       "8      26.540851      2.606046         0.546757        0.077959   \n",
       "9      25.127939      0.922511         0.481404        0.083250   \n",
       "\n",
       "  param_nb__var_smoothing                         params  split0_test_score  \\\n",
       "0                     1.0     {'nb__var_smoothing': 1.0}             0.8125   \n",
       "1                     0.1     {'nb__var_smoothing': 0.1}             0.8125   \n",
       "2                    0.01    {'nb__var_smoothing': 0.01}             0.8125   \n",
       "3                   0.001   {'nb__var_smoothing': 0.001}             0.8125   \n",
       "4                  0.0001  {'nb__var_smoothing': 0.0001}             0.8125   \n",
       "5                 0.00001   {'nb__var_smoothing': 1e-05}             0.8125   \n",
       "6                0.000001   {'nb__var_smoothing': 1e-06}             0.8125   \n",
       "7                     0.0   {'nb__var_smoothing': 1e-07}             0.8125   \n",
       "8                     0.0   {'nb__var_smoothing': 1e-08}             0.8125   \n",
       "9                     0.0   {'nb__var_smoothing': 1e-09}             0.8125   \n",
       "\n",
       "   split1_test_score  split2_test_score  split3_test_score  split4_test_score  \\\n",
       "0             0.8125             0.8750             1.0000             0.8750   \n",
       "1             0.7500             0.6875             0.8125             0.6875   \n",
       "2             0.7500             0.7500             0.8125             0.6875   \n",
       "3             0.6875             0.6875             0.8125             0.7500   \n",
       "4             0.6875             0.6875             0.8125             0.7500   \n",
       "5             0.6875             0.6875             0.8125             0.7500   \n",
       "6             0.7500             0.6875             0.8125             0.7500   \n",
       "7             0.7500             0.6875             0.8125             0.7500   \n",
       "8             0.6875             0.6875             0.8125             0.7500   \n",
       "9             0.6875             0.6875             0.8125             0.7500   \n",
       "\n",
       "   split5_test_score  split6_test_score  split7_test_score  split8_test_score  \\\n",
       "0             0.6875             0.8125             0.8750             0.8750   \n",
       "1             0.8750             0.6250             0.6875             0.8125   \n",
       "2             0.7500             0.6250             0.6250             0.8125   \n",
       "3             0.6875             0.6250             0.6250             0.7500   \n",
       "4             0.6875             0.6250             0.6250             0.7500   \n",
       "5             0.6875             0.6250             0.6250             0.7500   \n",
       "6             0.6875             0.6250             0.6250             0.7500   \n",
       "7             0.6875             0.6250             0.6250             0.7500   \n",
       "8             0.6875             0.6250             0.6250             0.7500   \n",
       "9             0.6875             0.6250             0.6250             0.7500   \n",
       "\n",
       "   split9_test_score  mean_test_score  std_test_score  rank_test_score  \n",
       "0             0.9375          0.85625        0.079304                1  \n",
       "1             0.7500          0.75000        0.073951                2  \n",
       "2             0.6875          0.73125        0.068750                3  \n",
       "3             0.6875          0.71250        0.063738                6  \n",
       "4             0.6875          0.71250        0.063738                6  \n",
       "5             0.6875          0.71250        0.063738                6  \n",
       "6             0.6875          0.71875        0.064043                4  \n",
       "7             0.6875          0.71875        0.064043                4  \n",
       "8             0.6875          0.71250        0.063738                6  \n",
       "9             0.6875          0.71250        0.063738                6  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(model_nb.cv_results_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.825"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_nb.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00        80\n",
      "           1       1.00      1.00      1.00        80\n",
      "\n",
      "    accuracy                           1.00       160\n",
      "   macro avg       1.00      1.00      1.00       160\n",
      "weighted avg       1.00      1.00      1.00       160\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Train report\")\n",
    "print(classification_report(y_train, model_nb.predict(X_train)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.88      0.75      0.81        20\n",
      "           1       0.78      0.90      0.84        20\n",
      "\n",
      "    accuracy                           0.82        40\n",
      "   macro avg       0.83      0.82      0.82        40\n",
      "weighted avg       0.83      0.82      0.82        40\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Test report\")\n",
    "print(classification_report(y_test, model_nb.predict(X_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "plt.figure(figsize=(9, 5))\n",
    "labels = np.unique(y_test)\n",
    "cm = confusion_matrix(y_test, model_nb.predict(X_test), labels=labels)\n",
    "sns.heatmap(cm, annot=True, square=True, cmap='Greens', cbar=False, xticklabels=labels, yticklabels=labels,\n",
    "            fmt=\"d\", annot_kws={\"fontsize\": 15})\n",
    "plt.title(f'III. 40 Data Uji: {model_nb.score(X_test, y_test):.3f}', fontsize=14)\n",
    "plt.xlabel('Prediction', fontsize=14)\n",
    "plt.ylabel('Actual', fontsize=14)\n",
    "plt.yticks(rotation=0, verticalalignment='center');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Hoax</th>\n",
       "      <th>NHoax</th>\n",
       "      <th>Kategori</th>\n",
       "      <th>Kode Berita</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9.978787e-01</td>\n",
       "      <td>2.121258e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.921095e-01</td>\n",
       "      <td>7.890465e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.988919e-01</td>\n",
       "      <td>2.011081e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.895717e-07</td>\n",
       "      <td>9.999995e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.714214e-04</td>\n",
       "      <td>9.997286e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.475659e-05</td>\n",
       "      <td>9.999352e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4.214968e-05</td>\n",
       "      <td>9.999579e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>9.973559e-01</td>\n",
       "      <td>2.644119e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.900491e-02</td>\n",
       "      <td>9.809951e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7.232950e-03</td>\n",
       "      <td>9.927671e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>9.999654e-01</td>\n",
       "      <td>3.463627e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>9.998960e-01</td>\n",
       "      <td>1.040389e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>9.999598e-01</td>\n",
       "      <td>4.019714e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>6.730410e-02</td>\n",
       "      <td>9.326959e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8.198996e-01</td>\n",
       "      <td>1.801004e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Hoax_99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>9.999994e-01</td>\n",
       "      <td>6.157662e-07</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>3.373028e-05</td>\n",
       "      <td>9.999663e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2.394242e-06</td>\n",
       "      <td>9.999976e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>9.999943e-01</td>\n",
       "      <td>5.682893e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>7.549168e-05</td>\n",
       "      <td>9.999245e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>9.897815e-01</td>\n",
       "      <td>1.021849e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2.486774e-01</td>\n",
       "      <td>7.513226e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>9.852082e-01</td>\n",
       "      <td>1.479177e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>9.999920e-01</td>\n",
       "      <td>7.958624e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>9.999999e-01</td>\n",
       "      <td>1.352798e-07</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>9.999830e-01</td>\n",
       "      <td>1.697364e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>8.363846e-01</td>\n",
       "      <td>1.636154e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2.589727e-03</td>\n",
       "      <td>9.974103e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>9.167088e-06</td>\n",
       "      <td>9.999908e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3.101177e-05</td>\n",
       "      <td>9.999690e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>9.970671e-01</td>\n",
       "      <td>2.932942e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>9.999997e-01</td>\n",
       "      <td>2.714850e-07</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>4.807075e-05</td>\n",
       "      <td>9.999519e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>4.296987e-02</td>\n",
       "      <td>9.570301e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>4.667106e-09</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.781798e-11</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>9.989121e-01</td>\n",
       "      <td>1.087910e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>8.668550e-08</td>\n",
       "      <td>9.999999e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1.865586e-06</td>\n",
       "      <td>9.999981e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>9.950511e-01</td>\n",
       "      <td>4.948891e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>3.600653e-06</td>\n",
       "      <td>9.999964e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>7.243226e-04</td>\n",
       "      <td>9.992757e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1.582515e-02</td>\n",
       "      <td>9.841749e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1.593887e-05</td>\n",
       "      <td>9.999841e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>4.967000e-01</td>\n",
       "      <td>5.033000e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Nhoax_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>3.623359e-03</td>\n",
       "      <td>9.963766e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>9.808375e-01</td>\n",
       "      <td>1.916254e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>9.986163e-01</td>\n",
       "      <td>1.383678e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2.422648e-03</td>\n",
       "      <td>9.975774e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1.171276e-04</td>\n",
       "      <td>9.998829e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>7.400920e-03</td>\n",
       "      <td>9.925991e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>9.423043e-09</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2.273477e-03</td>\n",
       "      <td>9.977265e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>3.066979e-01</td>\n",
       "      <td>6.933021e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Nhoax_29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>4.523315e-10</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>4.694014e-04</td>\n",
       "      <td>9.995306e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>9.935220e-01</td>\n",
       "      <td>6.478043e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.587041e-09</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>1.464913e-02</td>\n",
       "      <td>9.853509e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>6.436589e-01</td>\n",
       "      <td>3.563411e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>9.998863e-01</td>\n",
       "      <td>1.136704e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>9.999955e-01</td>\n",
       "      <td>4.542470e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>4.920567e-03</td>\n",
       "      <td>9.950794e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>9.843721e-01</td>\n",
       "      <td>1.562787e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>7.488936e-02</td>\n",
       "      <td>9.251106e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>3.918580e-05</td>\n",
       "      <td>9.999608e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>9.997988e-01</td>\n",
       "      <td>2.011630e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>3.160178e-01</td>\n",
       "      <td>6.839822e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>9.420119e-04</td>\n",
       "      <td>9.990580e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>9.988529e-01</td>\n",
       "      <td>1.147126e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>9.991338e-01</td>\n",
       "      <td>8.661678e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>9.573472e-01</td>\n",
       "      <td>4.265282e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>1.580940e-05</td>\n",
       "      <td>9.999842e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>9.998373e-01</td>\n",
       "      <td>1.626753e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>3.195308e-02</td>\n",
       "      <td>9.680469e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.567771e-08</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>5.575643e-03</td>\n",
       "      <td>9.944244e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>1.170941e-03</td>\n",
       "      <td>9.988291e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>9.997464e-01</td>\n",
       "      <td>2.535550e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>8.648120e-01</td>\n",
       "      <td>1.351880e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>9.922324e-01</td>\n",
       "      <td>7.767607e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>9.984730e-01</td>\n",
       "      <td>1.527025e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>9.998527e-01</td>\n",
       "      <td>1.472655e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>9.464988e-01</td>\n",
       "      <td>5.350117e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>7.316003e-05</td>\n",
       "      <td>9.999268e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>9.999925e-01</td>\n",
       "      <td>7.482307e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>2.585420e-01</td>\n",
       "      <td>7.414580e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>8.502670e-01</td>\n",
       "      <td>1.497330e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>9.924135e-01</td>\n",
       "      <td>7.586523e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>2.531078e-04</td>\n",
       "      <td>9.997469e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>9.994977e-01</td>\n",
       "      <td>5.023372e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>9.863076e-01</td>\n",
       "      <td>1.369241e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>9.999794e-01</td>\n",
       "      <td>2.058317e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>9.997877e-01</td>\n",
       "      <td>2.123105e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>5.199878e-02</td>\n",
       "      <td>9.480012e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>9.978960e-01</td>\n",
       "      <td>2.103978e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>2.461176e-06</td>\n",
       "      <td>9.999975e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>9.997506e-01</td>\n",
       "      <td>2.493729e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>7.308544e-02</td>\n",
       "      <td>9.269146e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>1.876275e-02</td>\n",
       "      <td>9.812372e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>3.731617e-06</td>\n",
       "      <td>9.999963e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>6.870829e-01</td>\n",
       "      <td>3.129171e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>9.999344e-01</td>\n",
       "      <td>6.562548e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>9.995470e-01</td>\n",
       "      <td>4.529676e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>3.658037e-03</td>\n",
       "      <td>9.963420e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>1.172910e-05</td>\n",
       "      <td>9.999883e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>9.991569e-01</td>\n",
       "      <td>8.430908e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>5.829251e-04</td>\n",
       "      <td>9.994171e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>3.994194e-04</td>\n",
       "      <td>9.996006e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2.283314e-06</td>\n",
       "      <td>9.999977e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>5.441645e-05</td>\n",
       "      <td>9.999456e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>1.160525e-04</td>\n",
       "      <td>9.998839e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>1.409154e-04</td>\n",
       "      <td>9.998591e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>9.991197e-01</td>\n",
       "      <td>8.802940e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>9.999801e-01</td>\n",
       "      <td>1.994790e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>9.999261e-01</td>\n",
       "      <td>7.387916e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>1.178425e-04</td>\n",
       "      <td>9.998822e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>9.999907e-01</td>\n",
       "      <td>9.309216e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>9.996684e-01</td>\n",
       "      <td>3.316297e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2.520633e-04</td>\n",
       "      <td>9.997479e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>2.749759e-09</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2.701338e-01</td>\n",
       "      <td>7.298662e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Nhoax_97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>9.999954e-01</td>\n",
       "      <td>4.605152e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.334575e-08</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2.765946e-02</td>\n",
       "      <td>9.723405e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>6.414732e-01</td>\n",
       "      <td>3.585268e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>9.980631e-01</td>\n",
       "      <td>1.936900e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>4.560977e-04</td>\n",
       "      <td>9.995439e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>4.087271e-05</td>\n",
       "      <td>9.999591e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>5.692961e-04</td>\n",
       "      <td>9.994307e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>9.832028e-01</td>\n",
       "      <td>1.679724e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>9.999998e-01</td>\n",
       "      <td>2.239013e-07</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>3.511187e-03</td>\n",
       "      <td>9.964888e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>9.998482e-01</td>\n",
       "      <td>1.518153e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>9.988052e-01</td>\n",
       "      <td>1.194785e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>5.733055e-06</td>\n",
       "      <td>9.999943e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>9.999301e-01</td>\n",
       "      <td>6.985473e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>1.591308e-03</td>\n",
       "      <td>9.984087e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>9.988094e-01</td>\n",
       "      <td>1.190622e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>9.310789e-01</td>\n",
       "      <td>6.892113e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2.690986e-08</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>6.477162e-06</td>\n",
       "      <td>9.999935e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>1.521806e-05</td>\n",
       "      <td>9.999848e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>5.964857e-03</td>\n",
       "      <td>9.940351e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>9.999866e-01</td>\n",
       "      <td>1.341520e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>9.999832e-01</td>\n",
       "      <td>1.683591e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>9.977615e-01</td>\n",
       "      <td>2.238472e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Hoax_93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>3.353715e-05</td>\n",
       "      <td>9.999665e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>3.507891e-01</td>\n",
       "      <td>6.492109e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Nhoax_94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>9.998720e-01</td>\n",
       "      <td>1.280021e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>2.703307e-04</td>\n",
       "      <td>9.997297e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>9.999956e-01</td>\n",
       "      <td>4.415262e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>9.997612e-01</td>\n",
       "      <td>2.387559e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>1.836773e-02</td>\n",
       "      <td>9.816323e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.649875e-09</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>2.862629e-03</td>\n",
       "      <td>9.971374e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>9.999297e-01</td>\n",
       "      <td>7.033708e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>9.658426e-04</td>\n",
       "      <td>9.990342e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>9.999931e-01</td>\n",
       "      <td>6.934829e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>6.385484e-04</td>\n",
       "      <td>9.993615e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>1.287608e-05</td>\n",
       "      <td>9.999871e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>9.997157e-01</td>\n",
       "      <td>2.842562e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>9.999927e-01</td>\n",
       "      <td>7.328315e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>3.824891e-03</td>\n",
       "      <td>9.961751e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>1.085439e-03</td>\n",
       "      <td>9.989146e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>9.998501e-01</td>\n",
       "      <td>1.499463e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>2.201182e-01</td>\n",
       "      <td>7.798818e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Nhoax_85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>4.668058e-06</td>\n",
       "      <td>9.999953e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>9.999738e-01</td>\n",
       "      <td>2.622920e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>1.360812e-02</td>\n",
       "      <td>9.863919e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>1.928882e-04</td>\n",
       "      <td>9.998071e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>2.006736e-06</td>\n",
       "      <td>9.999980e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>1.525958e-04</td>\n",
       "      <td>9.998474e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>9.252852e-01</td>\n",
       "      <td>7.471483e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>5.856791e-06</td>\n",
       "      <td>9.999941e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>3.418445e-06</td>\n",
       "      <td>9.999966e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>1.813805e-04</td>\n",
       "      <td>9.998186e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>1.587325e-03</td>\n",
       "      <td>9.984127e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>3.176349e-01</td>\n",
       "      <td>6.823651e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>1.575003e-02</td>\n",
       "      <td>9.842500e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>4.827886e-04</td>\n",
       "      <td>9.995172e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>2.967708e-08</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>9.460623e-01</td>\n",
       "      <td>5.393766e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>9.984981e-01</td>\n",
       "      <td>1.501900e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>9.989848e-01</td>\n",
       "      <td>1.015206e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>2.917445e-02</td>\n",
       "      <td>9.708256e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>9.999944e-01</td>\n",
       "      <td>5.645948e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>9.991900e-01</td>\n",
       "      <td>8.100436e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>8.314588e-01</td>\n",
       "      <td>1.685412e-01</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>9.999999e-01</td>\n",
       "      <td>1.018037e-07</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>9.999967e-01</td>\n",
       "      <td>3.346122e-06</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>3.538407e-01</td>\n",
       "      <td>6.461593e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>9.999142e-01</td>\n",
       "      <td>8.575446e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>9.999766e-01</td>\n",
       "      <td>2.335254e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>9.999062e-01</td>\n",
       "      <td>9.379920e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>2.279945e-03</td>\n",
       "      <td>9.977201e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>9.999413e-01</td>\n",
       "      <td>5.874355e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>6.813842e-07</td>\n",
       "      <td>9.999993e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>2.484394e-04</td>\n",
       "      <td>9.997516e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.966824e-09</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Hoax         NHoax Kategori Kode Berita\n",
       "0    9.978787e-01  2.121258e-03    NHoax    Nhoax_28\n",
       "1    9.921095e-01  7.890465e-03    NHoax    Nhoax_73\n",
       "2    7.988919e-01  2.011081e-01    NHoax     Nhoax_5\n",
       "3    4.895717e-07  9.999995e-01     Hoax      Hoax_3\n",
       "4    2.714214e-04  9.997286e-01     Hoax     Hoax_48\n",
       "5    6.475659e-05  9.999352e-01     Hoax     Hoax_65\n",
       "6    4.214968e-05  9.999579e-01     Hoax     Hoax_83\n",
       "7    9.973559e-01  2.644119e-03    NHoax    Nhoax_96\n",
       "8    1.900491e-02  9.809951e-01     Hoax      Hoax_7\n",
       "9    7.232950e-03  9.927671e-01     Hoax     Hoax_19\n",
       "10   9.999654e-01  3.463627e-05    NHoax    Nhoax_12\n",
       "11   9.998960e-01  1.040389e-04    NHoax    Nhoax_72\n",
       "12   9.999598e-01  4.019714e-05    NHoax    Nhoax_57\n",
       "13   6.730410e-02  9.326959e-01     Hoax     Hoax_82\n",
       "14   8.198996e-01  1.801004e-01    NHoax     Hoax_99\n",
       "15   9.999994e-01  6.157662e-07    NHoax    Nhoax_54\n",
       "16   3.373028e-05  9.999663e-01     Hoax     Hoax_67\n",
       "17   2.394242e-06  9.999976e-01     Hoax     Hoax_75\n",
       "18   9.999943e-01  5.682893e-06    NHoax     Nhoax_9\n",
       "19   7.549168e-05  9.999245e-01     Hoax     Hoax_77\n",
       "20   9.897815e-01  1.021849e-02    NHoax     Nhoax_1\n",
       "21   2.486774e-01  7.513226e-01     Hoax     Hoax_34\n",
       "22   9.852082e-01  1.479177e-02    NHoax    Nhoax_98\n",
       "23   9.999920e-01  7.958624e-06    NHoax    Nhoax_56\n",
       "24   9.999999e-01  1.352798e-07    NHoax    Nhoax_88\n",
       "25   9.999830e-01  1.697364e-05    NHoax    Nhoax_99\n",
       "26   8.363846e-01  1.636154e-01    NHoax    Nhoax_42\n",
       "27   2.589727e-03  9.974103e-01     Hoax     Hoax_63\n",
       "28   9.167088e-06  9.999908e-01     Hoax     Hoax_28\n",
       "29   3.101177e-05  9.999690e-01     Hoax     Hoax_58\n",
       "30   9.970671e-01  2.932942e-03    NHoax    Nhoax_38\n",
       "31   9.999997e-01  2.714850e-07    NHoax    Nhoax_41\n",
       "32   4.807075e-05  9.999519e-01     Hoax     Hoax_76\n",
       "33   4.296987e-02  9.570301e-01     Hoax      Hoax_5\n",
       "34   4.667106e-09  1.000000e+00     Hoax      Hoax_2\n",
       "35   1.000000e+00  1.781798e-11    NHoax    Nhoax_70\n",
       "36   9.989121e-01  1.087910e-03    NHoax     Nhoax_2\n",
       "37   8.668550e-08  9.999999e-01     Hoax     Hoax_45\n",
       "38   1.865586e-06  9.999981e-01     Hoax     Hoax_50\n",
       "39   9.950511e-01  4.948891e-03    NHoax    Nhoax_45\n",
       "40   3.600653e-06  9.999964e-01     Hoax     Hoax_51\n",
       "41   7.243226e-04  9.992757e-01     Hoax     Hoax_56\n",
       "42   1.582515e-02  9.841749e-01     Hoax     Hoax_36\n",
       "43   1.593887e-05  9.999841e-01     Hoax     Hoax_22\n",
       "44   4.967000e-01  5.033000e-01     Hoax     Nhoax_4\n",
       "45   3.623359e-03  9.963766e-01     Hoax     Hoax_32\n",
       "46   9.808375e-01  1.916254e-02    NHoax    Nhoax_74\n",
       "47   9.986163e-01  1.383678e-03    NHoax    Nhoax_68\n",
       "48   2.422648e-03  9.975774e-01     Hoax     Hoax_80\n",
       "49   1.171276e-04  9.998829e-01     Hoax     Hoax_89\n",
       "50   7.400920e-03  9.925991e-01     Hoax     Hoax_27\n",
       "51   9.423043e-09  1.000000e+00     Hoax     Hoax_29\n",
       "52   2.273477e-03  9.977265e-01     Hoax     Hoax_88\n",
       "53   3.066979e-01  6.933021e-01     Hoax    Nhoax_29\n",
       "54   4.523315e-10  1.000000e+00     Hoax      Hoax_6\n",
       "55   4.694014e-04  9.995306e-01     Hoax     Hoax_92\n",
       "56   9.935220e-01  6.478043e-03    NHoax    Nhoax_91\n",
       "57   1.000000e+00  3.587041e-09    NHoax    Nhoax_89\n",
       "58   1.464913e-02  9.853509e-01     Hoax     Hoax_74\n",
       "59   6.436589e-01  3.563411e-01    NHoax    Nhoax_66\n",
       "60   9.998863e-01  1.136704e-04    NHoax    Nhoax_64\n",
       "61   9.999955e-01  4.542470e-06    NHoax    Nhoax_90\n",
       "62   4.920567e-03  9.950794e-01     Hoax     Hoax_38\n",
       "63   9.843721e-01  1.562787e-02    NHoax    Nhoax_61\n",
       "64   7.488936e-02  9.251106e-01     Hoax     Hoax_44\n",
       "65   3.918580e-05  9.999608e-01     Hoax     Hoax_25\n",
       "66   9.997988e-01  2.011630e-04    NHoax    Nhoax_92\n",
       "67   3.160178e-01  6.839822e-01     Hoax     Hoax_12\n",
       "68   9.420119e-04  9.990580e-01     Hoax     Hoax_69\n",
       "69   9.988529e-01  1.147126e-03    NHoax    Nhoax_32\n",
       "70   9.991338e-01  8.661678e-04    NHoax    Nhoax_47\n",
       "71   9.573472e-01  4.265282e-02    NHoax    Nhoax_20\n",
       "72   1.580940e-05  9.999842e-01     Hoax     Hoax_23\n",
       "73   9.998373e-01  1.626753e-04    NHoax     Nhoax_7\n",
       "74   3.195308e-02  9.680469e-01     Hoax     Hoax_70\n",
       "75   1.000000e+00  1.567771e-08    NHoax     Nhoax_3\n",
       "76   5.575643e-03  9.944244e-01     Hoax     Hoax_87\n",
       "77   1.170941e-03  9.988291e-01     Hoax     Hoax_11\n",
       "78   9.997464e-01  2.535550e-04    NHoax    Nhoax_87\n",
       "79   8.648120e-01  1.351880e-01    NHoax    Nhoax_62\n",
       "80   9.922324e-01  7.767607e-03    NHoax    Nhoax_11\n",
       "81   9.984730e-01  1.527025e-03    NHoax    Nhoax_53\n",
       "82   9.998527e-01  1.472655e-04    NHoax    Nhoax_34\n",
       "83   9.464988e-01  5.350117e-02    NHoax    Nhoax_31\n",
       "84   7.316003e-05  9.999268e-01     Hoax     Hoax_14\n",
       "85   9.999925e-01  7.482307e-06    NHoax    Nhoax_44\n",
       "86   2.585420e-01  7.414580e-01     Hoax     Hoax_20\n",
       "87   8.502670e-01  1.497330e-01    NHoax    Nhoax_10\n",
       "88   9.924135e-01  7.586523e-03    NHoax    Nhoax_27\n",
       "89   2.531078e-04  9.997469e-01     Hoax     Hoax_35\n",
       "90   9.994977e-01  5.023372e-04    NHoax    Nhoax_39\n",
       "91   9.863076e-01  1.369241e-02    NHoax    Nhoax_46\n",
       "92   9.999794e-01  2.058317e-05    NHoax    Nhoax_19\n",
       "93   9.997877e-01  2.123105e-04    NHoax    Nhoax_50\n",
       "94   5.199878e-02  9.480012e-01     Hoax     Hoax_26\n",
       "95   9.978960e-01  2.103978e-03    NHoax    Nhoax_25\n",
       "96   2.461176e-06  9.999975e-01     Hoax     Hoax_18\n",
       "97   9.997506e-01  2.493729e-04    NHoax    Nhoax_84\n",
       "98   7.308544e-02  9.269146e-01     Hoax     Hoax_13\n",
       "99   1.876275e-02  9.812372e-01     Hoax     Hoax_21\n",
       "100  3.731617e-06  9.999963e-01     Hoax     Hoax_85\n",
       "101  6.870829e-01  3.129171e-01    NHoax    Nhoax_63\n",
       "102  9.999344e-01  6.562548e-05    NHoax    Nhoax_30\n",
       "103  9.995470e-01  4.529676e-04    NHoax    Nhoax_33\n",
       "104  3.658037e-03  9.963420e-01     Hoax     Hoax_95\n",
       "105  1.172910e-05  9.999883e-01     Hoax     Hoax_47\n",
       "106  9.991569e-01  8.430908e-04    NHoax    Nhoax_16\n",
       "107  5.829251e-04  9.994171e-01     Hoax     Hoax_86\n",
       "108  3.994194e-04  9.996006e-01     Hoax      Hoax_1\n",
       "109  2.283314e-06  9.999977e-01     Hoax    Hoax_100\n",
       "110  5.441645e-05  9.999456e-01     Hoax     Hoax_33\n",
       "111  1.160525e-04  9.998839e-01     Hoax     Hoax_24\n",
       "112  1.409154e-04  9.998591e-01     Hoax     Hoax_64\n",
       "113  9.991197e-01  8.802940e-04    NHoax    Nhoax_93\n",
       "114  9.999801e-01  1.994790e-05    NHoax     Nhoax_8\n",
       "115  9.999261e-01  7.387916e-05    NHoax    Nhoax_82\n",
       "116  1.178425e-04  9.998822e-01     Hoax     Hoax_43\n",
       "117  9.999907e-01  9.309216e-06    NHoax    Nhoax_58\n",
       "118  9.996684e-01  3.316297e-04    NHoax    Nhoax_49\n",
       "119  2.520633e-04  9.997479e-01     Hoax     Hoax_41\n",
       "120  2.749759e-09  1.000000e+00     Hoax     Hoax_62\n",
       "121  2.701338e-01  7.298662e-01     Hoax    Nhoax_97\n",
       "122  9.999954e-01  4.605152e-06    NHoax    Nhoax_71\n",
       "123  1.000000e+00  2.334575e-08    NHoax    Nhoax_83\n",
       "124  2.765946e-02  9.723405e-01     Hoax     Hoax_68\n",
       "125  6.414732e-01  3.585268e-01    NHoax    Nhoax_67\n",
       "126  9.980631e-01  1.936900e-03    NHoax    Nhoax_14\n",
       "127  4.560977e-04  9.995439e-01     Hoax     Hoax_81\n",
       "128  4.087271e-05  9.999591e-01     Hoax     Hoax_53\n",
       "129  5.692961e-04  9.994307e-01     Hoax      Hoax_4\n",
       "130  9.832028e-01  1.679724e-02    NHoax    Nhoax_59\n",
       "131  9.999998e-01  2.239013e-07    NHoax    Nhoax_22\n",
       "132  3.511187e-03  9.964888e-01     Hoax     Hoax_57\n",
       "133  9.998482e-01  1.518153e-04    NHoax    Nhoax_18\n",
       "134  9.988052e-01  1.194785e-03    NHoax    Nhoax_13\n",
       "135  5.733055e-06  9.999943e-01     Hoax     Hoax_55\n",
       "136  9.999301e-01  6.985473e-05    NHoax    Nhoax_36\n",
       "137  1.591308e-03  9.984087e-01     Hoax     Hoax_72\n",
       "138  9.988094e-01  1.190622e-03    NHoax     Nhoax_6\n",
       "139  9.310789e-01  6.892113e-02    NHoax    Nhoax_79\n",
       "140  2.690986e-08  1.000000e+00     Hoax     Hoax_97\n",
       "141  6.477162e-06  9.999935e-01     Hoax     Hoax_30\n",
       "142  1.521806e-05  9.999848e-01     Hoax     Hoax_78\n",
       "143  5.964857e-03  9.940351e-01     Hoax     Hoax_94\n",
       "144  9.999866e-01  1.341520e-05    NHoax   Nhoax_100\n",
       "145  9.999832e-01  1.683591e-05    NHoax    Nhoax_95\n",
       "146  9.977615e-01  2.238472e-03    NHoax     Hoax_93\n",
       "147  3.353715e-05  9.999665e-01     Hoax     Hoax_79\n",
       "148  3.507891e-01  6.492109e-01     Hoax    Nhoax_94\n",
       "149  9.998720e-01  1.280021e-04    NHoax    Nhoax_69\n",
       "150  2.703307e-04  9.997297e-01     Hoax     Hoax_52\n",
       "151  9.999956e-01  4.415262e-06    NHoax    Nhoax_65\n",
       "152  9.997612e-01  2.387559e-04    NHoax    Nhoax_78\n",
       "153  1.836773e-02  9.816323e-01     Hoax     Hoax_61\n",
       "154  1.000000e+00  2.649875e-09    NHoax    Nhoax_51\n",
       "155  2.862629e-03  9.971374e-01     Hoax     Hoax_16\n",
       "156  9.999297e-01  7.033708e-05    NHoax    Nhoax_48\n",
       "157  9.658426e-04  9.990342e-01     Hoax     Hoax_40\n",
       "158  9.999931e-01  6.934829e-06    NHoax    Nhoax_43\n",
       "159  6.385484e-04  9.993615e-01     Hoax     Hoax_59\n",
       "160  1.287608e-05  9.999871e-01     Hoax     Hoax_71\n",
       "161  9.997157e-01  2.842562e-04    NHoax    Nhoax_55\n",
       "162  9.999927e-01  7.328315e-06    NHoax    Nhoax_86\n",
       "163  3.824891e-03  9.961751e-01     Hoax     Hoax_73\n",
       "164  1.085439e-03  9.989146e-01     Hoax     Hoax_66\n",
       "165  9.998501e-01  1.499463e-04    NHoax    Nhoax_75\n",
       "166  2.201182e-01  7.798818e-01     Hoax    Nhoax_85\n",
       "167  4.668058e-06  9.999953e-01     Hoax     Hoax_10\n",
       "168  9.999738e-01  2.622920e-05    NHoax    Nhoax_15\n",
       "169  1.360812e-02  9.863919e-01     Hoax     Hoax_15\n",
       "170  1.928882e-04  9.998071e-01     Hoax     Hoax_31\n",
       "171  2.006736e-06  9.999980e-01     Hoax     Hoax_90\n",
       "172  1.525958e-04  9.998474e-01     Hoax     Hoax_98\n",
       "173  9.252852e-01  7.471483e-02    NHoax    Nhoax_24\n",
       "174  5.856791e-06  9.999941e-01     Hoax     Hoax_42\n",
       "175  3.418445e-06  9.999966e-01     Hoax     Hoax_49\n",
       "176  1.813805e-04  9.998186e-01     Hoax     Hoax_96\n",
       "177  1.587325e-03  9.984127e-01     Hoax      Hoax_8\n",
       "178  3.176349e-01  6.823651e-01     Hoax     Hoax_60\n",
       "179  1.575003e-02  9.842500e-01     Hoax     Hoax_84\n",
       "180  4.827886e-04  9.995172e-01     Hoax      Hoax_9\n",
       "181  2.967708e-08  1.000000e+00     Hoax     Hoax_91\n",
       "182  9.460623e-01  5.393766e-02    NHoax    Nhoax_52\n",
       "183  9.984981e-01  1.501900e-03    NHoax    Nhoax_35\n",
       "184  9.989848e-01  1.015206e-03    NHoax    Nhoax_37\n",
       "185  2.917445e-02  9.708256e-01     Hoax     Hoax_17\n",
       "186  9.999944e-01  5.645948e-06    NHoax    Nhoax_21\n",
       "187  9.991900e-01  8.100436e-04    NHoax    Nhoax_81\n",
       "188  8.314588e-01  1.685412e-01    NHoax    Nhoax_40\n",
       "189  9.999999e-01  1.018037e-07    NHoax    Nhoax_80\n",
       "190  9.999967e-01  3.346122e-06    NHoax    Nhoax_77\n",
       "191  3.538407e-01  6.461593e-01     Hoax     Hoax_37\n",
       "192  9.999142e-01  8.575446e-05    NHoax    Nhoax_23\n",
       "193  9.999766e-01  2.335254e-05    NHoax    Nhoax_76\n",
       "194  9.999062e-01  9.379920e-05    NHoax    Nhoax_17\n",
       "195  2.279945e-03  9.977201e-01     Hoax     Hoax_39\n",
       "196  9.999413e-01  5.874355e-05    NHoax    Nhoax_26\n",
       "197  6.813842e-07  9.999993e-01     Hoax     Hoax_46\n",
       "198  2.484394e-04  9.997516e-01     Hoax     Hoax_54\n",
       "199  1.000000e+00  5.966824e-09    NHoax    Nhoax_60"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_prob_nb = model_nb.predict_proba(X)\n",
    "pred_nb = model_nb.predict(X)\n",
    "nb_df = pd.DataFrame(data=pred_prob_nb,index=X.index,columns=['Hoax','NHoax'])\n",
    "nb_df['Kategori'] = pred_nb\n",
    "nb_df['Kategori'] = np.where(nb_df['Kategori'], 'Hoax', 'NHoax')\n",
    "nb_df['Kode Berita'] = df['Kode Berita']\n",
    "nb_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multinomial Naive Bayes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 10 folds for each of 20 candidates, totalling 200 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 8 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done  34 tasks      | elapsed:  4.0min\n",
      "[Parallel(n_jobs=-1)]: Done 184 tasks      | elapsed: 18.9min\n",
      "[Parallel(n_jobs=-1)]: Done 200 out of 200 | elapsed: 20.1min finished\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'mnb__alpha': 0.1, 'mnb__fit_prior': True}\n",
      "1.0 0.80625 0.875\n"
     ]
    }
   ],
   "source": [
    "pipeline = Pipeline([\n",
    "    ('prep', preprocessor),\n",
    "    ('mnb', MultinomialNB())\n",
    "])\n",
    "\n",
    "model_mnb = GridSearchCV(pipeline, params_mnb, cv=cv_method, n_jobs=-1, verbose=1)\n",
    "model_mnb.fit(X_train, y_train)\n",
    "\n",
    "print(model_mnb.best_params_)\n",
    "print(model_mnb.score(X_train, y_train), model_mnb.best_score_, model_mnb.score(X_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_mnb__alpha</th>\n",
       "      <th>param_mnb__fit_prior</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>split3_test_score</th>\n",
       "      <th>split4_test_score</th>\n",
       "      <th>split5_test_score</th>\n",
       "      <th>split6_test_score</th>\n",
       "      <th>split7_test_score</th>\n",
       "      <th>split8_test_score</th>\n",
       "      <th>split9_test_score</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>47.381975</td>\n",
       "      <td>12.833103</td>\n",
       "      <td>1.303029</td>\n",
       "      <td>0.516991</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 1.0, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.78750</td>\n",
       "      <td>0.075000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>61.773336</td>\n",
       "      <td>22.553760</td>\n",
       "      <td>1.259237</td>\n",
       "      <td>0.485443</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 1.0, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.78750</td>\n",
       "      <td>0.075000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41.550524</td>\n",
       "      <td>15.368124</td>\n",
       "      <td>0.732545</td>\n",
       "      <td>0.424930</td>\n",
       "      <td>0.1</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 0.1, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.80625</td>\n",
       "      <td>0.065252</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49.689642</td>\n",
       "      <td>16.219845</td>\n",
       "      <td>0.831706</td>\n",
       "      <td>0.356658</td>\n",
       "      <td>0.1</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 0.1, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.80625</td>\n",
       "      <td>0.065252</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31.711308</td>\n",
       "      <td>5.437458</td>\n",
       "      <td>0.616396</td>\n",
       "      <td>0.214253</td>\n",
       "      <td>0.01</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 0.01, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.79375</td>\n",
       "      <td>0.084085</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>31.643942</td>\n",
       "      <td>7.122338</td>\n",
       "      <td>0.684576</td>\n",
       "      <td>0.345215</td>\n",
       "      <td>0.01</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 0.01, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.79375</td>\n",
       "      <td>0.084085</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>41.160048</td>\n",
       "      <td>16.624532</td>\n",
       "      <td>0.623824</td>\n",
       "      <td>0.320048</td>\n",
       "      <td>0.001</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 0.001, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.76875</td>\n",
       "      <td>0.084085</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>41.551144</td>\n",
       "      <td>14.605904</td>\n",
       "      <td>0.822038</td>\n",
       "      <td>0.389175</td>\n",
       "      <td>0.001</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 0.001, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.76875</td>\n",
       "      <td>0.084085</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>56.303744</td>\n",
       "      <td>17.468247</td>\n",
       "      <td>1.049460</td>\n",
       "      <td>0.561424</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 0.0001, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.76875</td>\n",
       "      <td>0.084085</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>48.291426</td>\n",
       "      <td>11.979208</td>\n",
       "      <td>0.647449</td>\n",
       "      <td>0.312840</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 0.0001, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.76875</td>\n",
       "      <td>0.084085</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>46.251409</td>\n",
       "      <td>8.675410</td>\n",
       "      <td>1.137513</td>\n",
       "      <td>0.457296</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 1e-05, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.76875</td>\n",
       "      <td>0.084085</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>47.615907</td>\n",
       "      <td>13.663469</td>\n",
       "      <td>0.959724</td>\n",
       "      <td>0.525499</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 1e-05, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.76875</td>\n",
       "      <td>0.084085</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>58.390499</td>\n",
       "      <td>19.972875</td>\n",
       "      <td>1.164155</td>\n",
       "      <td>0.529917</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 1e-06, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.75000</td>\n",
       "      <td>0.079057</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>52.892891</td>\n",
       "      <td>16.382834</td>\n",
       "      <td>0.958194</td>\n",
       "      <td>0.520173</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 1e-06, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.75000</td>\n",
       "      <td>0.079057</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>42.280092</td>\n",
       "      <td>19.120776</td>\n",
       "      <td>0.755842</td>\n",
       "      <td>0.452584</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 1e-07, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.74375</td>\n",
       "      <td>0.081250</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>49.265981</td>\n",
       "      <td>22.502546</td>\n",
       "      <td>1.064680</td>\n",
       "      <td>0.538410</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 1e-07, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.74375</td>\n",
       "      <td>0.081250</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>49.007052</td>\n",
       "      <td>19.540407</td>\n",
       "      <td>0.960192</td>\n",
       "      <td>0.542789</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 1e-08, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.74375</td>\n",
       "      <td>0.081250</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>53.028791</td>\n",
       "      <td>22.976953</td>\n",
       "      <td>1.021265</td>\n",
       "      <td>0.514364</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 1e-08, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.74375</td>\n",
       "      <td>0.081250</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>46.085436</td>\n",
       "      <td>22.226837</td>\n",
       "      <td>0.950597</td>\n",
       "      <td>0.536724</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>{'mnb__alpha': 1e-09, 'mnb__fit_prior': True}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.74375</td>\n",
       "      <td>0.081250</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>37.673976</td>\n",
       "      <td>15.042511</td>\n",
       "      <td>0.608386</td>\n",
       "      <td>0.194200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>{'mnb__alpha': 1e-09, 'mnb__fit_prior': False}</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.8750</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.6250</td>\n",
       "      <td>0.7500</td>\n",
       "      <td>0.6875</td>\n",
       "      <td>0.74375</td>\n",
       "      <td>0.081250</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
       "0       47.381975     12.833103         1.303029        0.516991   \n",
       "1       61.773336     22.553760         1.259237        0.485443   \n",
       "2       41.550524     15.368124         0.732545        0.424930   \n",
       "3       49.689642     16.219845         0.831706        0.356658   \n",
       "4       31.711308      5.437458         0.616396        0.214253   \n",
       "5       31.643942      7.122338         0.684576        0.345215   \n",
       "6       41.160048     16.624532         0.623824        0.320048   \n",
       "7       41.551144     14.605904         0.822038        0.389175   \n",
       "8       56.303744     17.468247         1.049460        0.561424   \n",
       "9       48.291426     11.979208         0.647449        0.312840   \n",
       "10      46.251409      8.675410         1.137513        0.457296   \n",
       "11      47.615907     13.663469         0.959724        0.525499   \n",
       "12      58.390499     19.972875         1.164155        0.529917   \n",
       "13      52.892891     16.382834         0.958194        0.520173   \n",
       "14      42.280092     19.120776         0.755842        0.452584   \n",
       "15      49.265981     22.502546         1.064680        0.538410   \n",
       "16      49.007052     19.540407         0.960192        0.542789   \n",
       "17      53.028791     22.976953         1.021265        0.514364   \n",
       "18      46.085436     22.226837         0.950597        0.536724   \n",
       "19      37.673976     15.042511         0.608386        0.194200   \n",
       "\n",
       "   param_mnb__alpha param_mnb__fit_prior  \\\n",
       "0               1.0                 True   \n",
       "1               1.0                False   \n",
       "2               0.1                 True   \n",
       "3               0.1                False   \n",
       "4              0.01                 True   \n",
       "5              0.01                False   \n",
       "6             0.001                 True   \n",
       "7             0.001                False   \n",
       "8            0.0001                 True   \n",
       "9            0.0001                False   \n",
       "10          0.00001                 True   \n",
       "11          0.00001                False   \n",
       "12         0.000001                 True   \n",
       "13         0.000001                False   \n",
       "14              0.0                 True   \n",
       "15              0.0                False   \n",
       "16              0.0                 True   \n",
       "17              0.0                False   \n",
       "18              0.0                 True   \n",
       "19              0.0                False   \n",
       "\n",
       "                                             params  split0_test_score  \\\n",
       "0       {'mnb__alpha': 1.0, 'mnb__fit_prior': True}             0.8125   \n",
       "1      {'mnb__alpha': 1.0, 'mnb__fit_prior': False}             0.8125   \n",
       "2       {'mnb__alpha': 0.1, 'mnb__fit_prior': True}             0.8125   \n",
       "3      {'mnb__alpha': 0.1, 'mnb__fit_prior': False}             0.8125   \n",
       "4      {'mnb__alpha': 0.01, 'mnb__fit_prior': True}             0.8125   \n",
       "5     {'mnb__alpha': 0.01, 'mnb__fit_prior': False}             0.8125   \n",
       "6     {'mnb__alpha': 0.001, 'mnb__fit_prior': True}             0.8125   \n",
       "7    {'mnb__alpha': 0.001, 'mnb__fit_prior': False}             0.8125   \n",
       "8    {'mnb__alpha': 0.0001, 'mnb__fit_prior': True}             0.8125   \n",
       "9   {'mnb__alpha': 0.0001, 'mnb__fit_prior': False}             0.8125   \n",
       "10    {'mnb__alpha': 1e-05, 'mnb__fit_prior': True}             0.8125   \n",
       "11   {'mnb__alpha': 1e-05, 'mnb__fit_prior': False}             0.8125   \n",
       "12    {'mnb__alpha': 1e-06, 'mnb__fit_prior': True}             0.8125   \n",
       "13   {'mnb__alpha': 1e-06, 'mnb__fit_prior': False}             0.8125   \n",
       "14    {'mnb__alpha': 1e-07, 'mnb__fit_prior': True}             0.8125   \n",
       "15   {'mnb__alpha': 1e-07, 'mnb__fit_prior': False}             0.8125   \n",
       "16    {'mnb__alpha': 1e-08, 'mnb__fit_prior': True}             0.8125   \n",
       "17   {'mnb__alpha': 1e-08, 'mnb__fit_prior': False}             0.8125   \n",
       "18    {'mnb__alpha': 1e-09, 'mnb__fit_prior': True}             0.8125   \n",
       "19   {'mnb__alpha': 1e-09, 'mnb__fit_prior': False}             0.8125   \n",
       "\n",
       "    split1_test_score  split2_test_score  split3_test_score  \\\n",
       "0              0.8125             0.6875             0.8750   \n",
       "1              0.8125             0.6875             0.8750   \n",
       "2              0.8125             0.8750             0.8750   \n",
       "3              0.8125             0.8750             0.8750   \n",
       "4              0.7500             0.8125             0.8750   \n",
       "5              0.7500             0.8125             0.8750   \n",
       "6              0.7500             0.8125             0.8125   \n",
       "7              0.7500             0.8125             0.8125   \n",
       "8              0.7500             0.8125             0.8125   \n",
       "9              0.7500             0.8125             0.8125   \n",
       "10             0.7500             0.8125             0.8125   \n",
       "11             0.7500             0.8125             0.8125   \n",
       "12             0.7500             0.8125             0.8125   \n",
       "13             0.7500             0.8125             0.8125   \n",
       "14             0.6875             0.8125             0.8125   \n",
       "15             0.6875             0.8125             0.8125   \n",
       "16             0.6875             0.8125             0.8125   \n",
       "17             0.6875             0.8125             0.8125   \n",
       "18             0.6875             0.8125             0.8125   \n",
       "19             0.6875             0.8125             0.8125   \n",
       "\n",
       "    split4_test_score  split5_test_score  split6_test_score  \\\n",
       "0              0.8750             0.8125             0.6250   \n",
       "1              0.8750             0.8125             0.6250   \n",
       "2              0.8125             0.8750             0.6875   \n",
       "3              0.8125             0.8750             0.6875   \n",
       "4              0.8125             0.9375             0.6250   \n",
       "5              0.8125             0.9375             0.6250   \n",
       "6              0.7500             0.9375             0.6250   \n",
       "7              0.7500             0.9375             0.6250   \n",
       "8              0.7500             0.9375             0.6250   \n",
       "9              0.7500             0.9375             0.6250   \n",
       "10             0.7500             0.9375             0.6250   \n",
       "11             0.7500             0.9375             0.6250   \n",
       "12             0.7500             0.8750             0.6250   \n",
       "13             0.7500             0.8750             0.6250   \n",
       "14             0.7500             0.8750             0.6250   \n",
       "15             0.7500             0.8750             0.6250   \n",
       "16             0.7500             0.8750             0.6250   \n",
       "17             0.7500             0.8750             0.6250   \n",
       "18             0.7500             0.8750             0.6250   \n",
       "19             0.7500             0.8750             0.6250   \n",
       "\n",
       "    split7_test_score  split8_test_score  split9_test_score  mean_test_score  \\\n",
       "0              0.7500             0.8125             0.8125          0.78750   \n",
       "1              0.7500             0.8125             0.8125          0.78750   \n",
       "2              0.6875             0.8125             0.8125          0.80625   \n",
       "3              0.6875             0.8125             0.8125          0.80625   \n",
       "4              0.6875             0.8125             0.8125          0.79375   \n",
       "5              0.6875             0.8125             0.8125          0.79375   \n",
       "6              0.6875             0.8125             0.6875          0.76875   \n",
       "7              0.6875             0.8125             0.6875          0.76875   \n",
       "8              0.6875             0.8125             0.6875          0.76875   \n",
       "9              0.6875             0.8125             0.6875          0.76875   \n",
       "10             0.6875             0.8125             0.6875          0.76875   \n",
       "11             0.6875             0.8125             0.6875          0.76875   \n",
       "12             0.6250             0.7500             0.6875          0.75000   \n",
       "13             0.6250             0.7500             0.6875          0.75000   \n",
       "14             0.6250             0.7500             0.6875          0.74375   \n",
       "15             0.6250             0.7500             0.6875          0.74375   \n",
       "16             0.6250             0.7500             0.6875          0.74375   \n",
       "17             0.6250             0.7500             0.6875          0.74375   \n",
       "18             0.6250             0.7500             0.6875          0.74375   \n",
       "19             0.6250             0.7500             0.6875          0.74375   \n",
       "\n",
       "    std_test_score  rank_test_score  \n",
       "0         0.075000                5  \n",
       "1         0.075000                5  \n",
       "2         0.065252                1  \n",
       "3         0.065252                1  \n",
       "4         0.084085                3  \n",
       "5         0.084085                3  \n",
       "6         0.084085                7  \n",
       "7         0.084085                7  \n",
       "8         0.084085                7  \n",
       "9         0.084085                7  \n",
       "10        0.084085                7  \n",
       "11        0.084085                7  \n",
       "12        0.079057               13  \n",
       "13        0.079057               13  \n",
       "14        0.081250               15  \n",
       "15        0.081250               15  \n",
       "16        0.081250               15  \n",
       "17        0.081250               15  \n",
       "18        0.081250               15  \n",
       "19        0.081250               15  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(model_mnb.cv_results_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.875"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_mnb.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00        80\n",
      "           1       1.00      1.00      1.00        80\n",
      "\n",
      "    accuracy                           1.00       160\n",
      "   macro avg       1.00      1.00      1.00       160\n",
      "weighted avg       1.00      1.00      1.00       160\n",
      "\n",
      "\n",
      "Test report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.80      1.00      0.89        20\n",
      "           1       1.00      0.75      0.86        20\n",
      "\n",
      "    accuracy                           0.88        40\n",
      "   macro avg       0.90      0.88      0.87        40\n",
      "weighted avg       0.90      0.88      0.87        40\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Train report\")\n",
    "print(classification_report(y_train, model_mnb.predict(X_train)))\n",
    "print()\n",
    "print(\"Test report\")\n",
    "print(classification_report(y_test, model_mnb.predict(X_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Hoax</th>\n",
       "      <th>NHoax</th>\n",
       "      <th>Kategori</th>\n",
       "      <th>Kode Berita</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>9.282233e-16</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.998959e-01</td>\n",
       "      <td>1.040839e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.995868e-01</td>\n",
       "      <td>4.132447e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.210279e-27</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.745966e-14</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4.960876e-26</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2.230528e-22</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.808381e-19</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5.440804e-02</td>\n",
       "      <td>9.455920e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7.953337e-20</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.066179e-19</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.124637e-16</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.813322e-27</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>9.093612e-01</td>\n",
       "      <td>9.063879e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Hoax_82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.454495e-09</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Hoax_99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.986235e-24</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2.913082e-19</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1.893022e-31</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.596668e-30</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>7.642081e-24</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.821360e-10</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>3.811518e-06</td>\n",
       "      <td>9.999962e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>9.123483e-13</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>8.650274e-25</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.789700e-31</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.990943e-34</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>6.672561e-10</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2.614289e-13</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>3.496589e-33</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>4.798511e-32</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.005026e-20</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.642303e-27</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1.106846e-15</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>5.025268e-12</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>4.072463e-32</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.137249e-39</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.948677e-19</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1.057917e-40</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>7.345513e-31</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.526189e-14</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1.059047e-26</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>4.974452e-19</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2.573245e-10</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>3.799401e-24</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>9.275070e-01</td>\n",
       "      <td>7.249299e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>5.264838e-06</td>\n",
       "      <td>9.999947e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>9.999814e-01</td>\n",
       "      <td>1.862246e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.477068e-16</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>1.762101e-08</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>8.830407e-17</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>6.756021e-11</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>6.716890e-42</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2.289100e-07</td>\n",
       "      <td>9.999998e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>9.978156e-01</td>\n",
       "      <td>2.184433e-03</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>4.181843e-40</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>3.013599e-12</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>6.096404e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.161170e-32</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>8.668286e-04</td>\n",
       "      <td>9.991332e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.955221e-11</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.394175e-23</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.483237e-28</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>5.751855e-04</td>\n",
       "      <td>9.994248e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>9.999525e-01</td>\n",
       "      <td>4.749075e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>4.236095e-02</td>\n",
       "      <td>9.576390e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>1.845812e-30</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.667761e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>9.994883e-01</td>\n",
       "      <td>5.117225e-04</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Hoax_12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>1.506981e-09</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>9.926294e-11</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>8.572750e-12</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.894692e-15</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>4.931614e-20</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.922044e-26</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>1.268147e-07</td>\n",
       "      <td>9.999999e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.811508e-24</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>7.923523e-08</td>\n",
       "      <td>9.999999e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>5.975430e-17</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.800518e-19</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>9.864670e-01</td>\n",
       "      <td>1.353305e-02</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.038410e-15</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.403436e-25</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.793455e-18</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>6.079840e-11</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>1.422858e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>8.254233e-16</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>9.999889e-01</td>\n",
       "      <td>1.113213e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Hoax_20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>8.033862e-16</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.782139e-17</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>8.685699e-17</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.773555e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.501863e-15</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>6.708798e-18</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.300368e-17</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>1.602542e-10</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>8.054188e-15</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>5.295947e-22</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.297508e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>3.401246e-06</td>\n",
       "      <td>9.999966e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>4.183289e-08</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>1.815408e-28</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>9.999996e-01</td>\n",
       "      <td>4.387367e-07</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.740127e-14</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.982544e-15</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>3.033333e-08</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>3.472929e-18</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.549554e-16</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>1.012550e-15</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>7.306241e-18</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>1.135144e-39</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>1.013460e-14</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>1.045265e-20</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>1.940402e-23</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>6.231710e-20</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.324949e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.779885e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>8.038707e-20</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.762504e-23</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.690934e-24</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2.445756e-23</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>5.628392e-44</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>9.999762e-01</td>\n",
       "      <td>2.377620e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.333818e-26</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.179742e-34</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>1.267684e-03</td>\n",
       "      <td>9.987323e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>9.999753e-01</td>\n",
       "      <td>2.469286e-05</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.793353e-17</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>9.633983e-13</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>8.135698e-17</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1.151840e-17</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.699633e-15</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.704802e-37</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>4.629139e-04</td>\n",
       "      <td>9.995371e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.566689e-22</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.761569e-11</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>3.270085e-24</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.272516e-14</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>3.220320e-09</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>8.892243e-12</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>9.999997e-01</td>\n",
       "      <td>2.988360e-07</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2.241779e-42</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2.361427e-21</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>3.878435e-35</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>3.501739e-06</td>\n",
       "      <td>9.999965e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.656229e-20</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.904179e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.845961e-12</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Hoax_93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>1.106275e-30</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>9.999993e-01</td>\n",
       "      <td>7.483021e-07</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.226192e-19</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>1.569458e-09</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.619520e-22</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.868535e-26</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>1.294651e-09</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.014466e-38</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>4.676628e-10</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.358074e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>6.380737e-15</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.284781e-28</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>2.232953e-15</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>1.106865e-20</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.166109e-25</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.026599e-15</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>4.773559e-08</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>3.771685e-13</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>6.622514e-19</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.844827e-08</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>1.752015e-18</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.639639e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>7.466066e-06</td>\n",
       "      <td>9.999925e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>9.040638e-13</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>2.509218e-28</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>9.631704e-19</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.357086e-08</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>9.162767e-29</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>9.753454e-22</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>4.549459e-13</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>4.639152e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>3.792649e-01</td>\n",
       "      <td>6.207351e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>1.055226e-04</td>\n",
       "      <td>9.998945e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>3.406629e-13</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>6.143118e-44</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.859308e-10</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.095878e-13</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.361690e-16</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>3.175808e-03</td>\n",
       "      <td>9.968242e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.354453e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.436338e-14</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.020876e-13</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.050587e-26</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.308253e-20</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>4.455330e-04</td>\n",
       "      <td>9.995545e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.438090e-20</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.280288e-21</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>9.516116e-19</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>7.535938e-05</td>\n",
       "      <td>9.999246e-01</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>9.522595e-22</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>4.427992e-22</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>9.409464e-10</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>Hoax</td>\n",
       "      <td>Hoax_54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.846114e-38</td>\n",
       "      <td>NHoax</td>\n",
       "      <td>Nhoax_60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Hoax         NHoax Kategori Kode Berita\n",
       "0    1.000000e+00  9.282233e-16    NHoax    Nhoax_28\n",
       "1    9.998959e-01  1.040839e-04    NHoax    Nhoax_73\n",
       "2    9.995868e-01  4.132447e-04    NHoax     Nhoax_5\n",
       "3    1.210279e-27  1.000000e+00     Hoax      Hoax_3\n",
       "4    1.745966e-14  1.000000e+00     Hoax     Hoax_48\n",
       "5    4.960876e-26  1.000000e+00     Hoax     Hoax_65\n",
       "6    2.230528e-22  1.000000e+00     Hoax     Hoax_83\n",
       "7    1.000000e+00  7.808381e-19    NHoax    Nhoax_96\n",
       "8    5.440804e-02  9.455920e-01     Hoax      Hoax_7\n",
       "9    7.953337e-20  1.000000e+00     Hoax     Hoax_19\n",
       "10   1.000000e+00  7.066179e-19    NHoax    Nhoax_12\n",
       "11   1.000000e+00  1.124637e-16    NHoax    Nhoax_72\n",
       "12   1.000000e+00  5.813322e-27    NHoax    Nhoax_57\n",
       "13   9.093612e-01  9.063879e-02    NHoax     Hoax_82\n",
       "14   1.000000e+00  4.454495e-09    NHoax     Hoax_99\n",
       "15   1.000000e+00  3.986235e-24    NHoax    Nhoax_54\n",
       "16   2.913082e-19  1.000000e+00     Hoax     Hoax_67\n",
       "17   1.893022e-31  1.000000e+00     Hoax     Hoax_75\n",
       "18   1.000000e+00  7.596668e-30    NHoax     Nhoax_9\n",
       "19   7.642081e-24  1.000000e+00     Hoax     Hoax_77\n",
       "20   1.000000e+00  2.821360e-10    NHoax     Nhoax_1\n",
       "21   3.811518e-06  9.999962e-01     Hoax     Hoax_34\n",
       "22   1.000000e+00  9.123483e-13    NHoax    Nhoax_98\n",
       "23   1.000000e+00  8.650274e-25    NHoax    Nhoax_56\n",
       "24   1.000000e+00  1.789700e-31    NHoax    Nhoax_88\n",
       "25   1.000000e+00  1.990943e-34    NHoax    Nhoax_99\n",
       "26   1.000000e+00  6.672561e-10    NHoax    Nhoax_42\n",
       "27   2.614289e-13  1.000000e+00     Hoax     Hoax_63\n",
       "28   3.496589e-33  1.000000e+00     Hoax     Hoax_28\n",
       "29   4.798511e-32  1.000000e+00     Hoax     Hoax_58\n",
       "30   1.000000e+00  1.005026e-20    NHoax    Nhoax_38\n",
       "31   1.000000e+00  2.642303e-27    NHoax    Nhoax_41\n",
       "32   1.106846e-15  1.000000e+00     Hoax     Hoax_76\n",
       "33   5.025268e-12  1.000000e+00     Hoax      Hoax_5\n",
       "34   4.072463e-32  1.000000e+00     Hoax      Hoax_2\n",
       "35   1.000000e+00  7.137249e-39    NHoax    Nhoax_70\n",
       "36   1.000000e+00  7.948677e-19    NHoax     Nhoax_2\n",
       "37   1.057917e-40  1.000000e+00     Hoax     Hoax_45\n",
       "38   7.345513e-31  1.000000e+00     Hoax     Hoax_50\n",
       "39   1.000000e+00  5.526189e-14    NHoax    Nhoax_45\n",
       "40   1.059047e-26  1.000000e+00     Hoax     Hoax_51\n",
       "41   4.974452e-19  1.000000e+00     Hoax     Hoax_56\n",
       "42   2.573245e-10  1.000000e+00     Hoax     Hoax_36\n",
       "43   3.799401e-24  1.000000e+00     Hoax     Hoax_22\n",
       "44   9.275070e-01  7.249299e-02    NHoax     Nhoax_4\n",
       "45   5.264838e-06  9.999947e-01     Hoax     Hoax_32\n",
       "46   9.999814e-01  1.862246e-05    NHoax    Nhoax_74\n",
       "47   1.000000e+00  1.477068e-16    NHoax    Nhoax_68\n",
       "48   1.762101e-08  1.000000e+00     Hoax     Hoax_80\n",
       "49   8.830407e-17  1.000000e+00     Hoax     Hoax_89\n",
       "50   6.756021e-11  1.000000e+00     Hoax     Hoax_27\n",
       "51   6.716890e-42  1.000000e+00     Hoax     Hoax_29\n",
       "52   2.289100e-07  9.999998e-01     Hoax     Hoax_88\n",
       "53   9.978156e-01  2.184433e-03    NHoax    Nhoax_29\n",
       "54   4.181843e-40  1.000000e+00     Hoax      Hoax_6\n",
       "55   3.013599e-12  1.000000e+00     Hoax     Hoax_92\n",
       "56   1.000000e+00  6.096404e-21    NHoax    Nhoax_91\n",
       "57   1.000000e+00  3.161170e-32    NHoax    Nhoax_89\n",
       "58   8.668286e-04  9.991332e-01     Hoax     Hoax_74\n",
       "59   1.000000e+00  1.955221e-11    NHoax    Nhoax_66\n",
       "60   1.000000e+00  1.394175e-23    NHoax    Nhoax_64\n",
       "61   1.000000e+00  1.483237e-28    NHoax    Nhoax_90\n",
       "62   5.751855e-04  9.994248e-01     Hoax     Hoax_38\n",
       "63   9.999525e-01  4.749075e-05    NHoax    Nhoax_61\n",
       "64   4.236095e-02  9.576390e-01     Hoax     Hoax_44\n",
       "65   1.845812e-30  1.000000e+00     Hoax     Hoax_25\n",
       "66   1.000000e+00  3.667761e-21    NHoax    Nhoax_92\n",
       "67   9.994883e-01  5.117225e-04    NHoax     Hoax_12\n",
       "68   1.506981e-09  1.000000e+00     Hoax     Hoax_69\n",
       "69   1.000000e+00  9.926294e-11    NHoax    Nhoax_32\n",
       "70   1.000000e+00  8.572750e-12    NHoax    Nhoax_47\n",
       "71   1.000000e+00  1.894692e-15    NHoax    Nhoax_20\n",
       "72   4.931614e-20  1.000000e+00     Hoax     Hoax_23\n",
       "73   1.000000e+00  2.922044e-26    NHoax     Nhoax_7\n",
       "74   1.268147e-07  9.999999e-01     Hoax     Hoax_70\n",
       "75   1.000000e+00  2.811508e-24    NHoax     Nhoax_3\n",
       "76   7.923523e-08  9.999999e-01     Hoax     Hoax_87\n",
       "77   5.975430e-17  1.000000e+00     Hoax     Hoax_11\n",
       "78   1.000000e+00  1.800518e-19    NHoax    Nhoax_87\n",
       "79   9.864670e-01  1.353305e-02    NHoax    Nhoax_62\n",
       "80   1.000000e+00  1.038410e-15    NHoax    Nhoax_11\n",
       "81   1.000000e+00  5.403436e-25    NHoax    Nhoax_53\n",
       "82   1.000000e+00  3.793455e-18    NHoax    Nhoax_34\n",
       "83   1.000000e+00  6.079840e-11    NHoax    Nhoax_31\n",
       "84   1.422858e-16  1.000000e+00     Hoax     Hoax_14\n",
       "85   1.000000e+00  8.254233e-16    NHoax    Nhoax_44\n",
       "86   9.999889e-01  1.113213e-05    NHoax     Hoax_20\n",
       "87   1.000000e+00  8.033862e-16    NHoax    Nhoax_10\n",
       "88   1.000000e+00  4.782139e-17    NHoax    Nhoax_27\n",
       "89   8.685699e-17  1.000000e+00     Hoax     Hoax_35\n",
       "90   1.000000e+00  3.773555e-21    NHoax    Nhoax_39\n",
       "91   1.000000e+00  4.501863e-15    NHoax    Nhoax_46\n",
       "92   1.000000e+00  6.708798e-18    NHoax    Nhoax_19\n",
       "93   1.000000e+00  5.300368e-17    NHoax    Nhoax_50\n",
       "94   1.602542e-10  1.000000e+00     Hoax     Hoax_26\n",
       "95   1.000000e+00  8.054188e-15    NHoax    Nhoax_25\n",
       "96   5.295947e-22  1.000000e+00     Hoax     Hoax_18\n",
       "97   1.000000e+00  2.297508e-21    NHoax    Nhoax_84\n",
       "98   3.401246e-06  9.999966e-01     Hoax     Hoax_13\n",
       "99   4.183289e-08  1.000000e+00     Hoax     Hoax_21\n",
       "100  1.815408e-28  1.000000e+00     Hoax     Hoax_85\n",
       "101  9.999996e-01  4.387367e-07    NHoax    Nhoax_63\n",
       "102  1.000000e+00  3.740127e-14    NHoax    Nhoax_30\n",
       "103  1.000000e+00  3.982544e-15    NHoax    Nhoax_33\n",
       "104  3.033333e-08  1.000000e+00     Hoax     Hoax_95\n",
       "105  3.472929e-18  1.000000e+00     Hoax     Hoax_47\n",
       "106  1.000000e+00  1.549554e-16    NHoax    Nhoax_16\n",
       "107  1.012550e-15  1.000000e+00     Hoax     Hoax_86\n",
       "108  7.306241e-18  1.000000e+00     Hoax      Hoax_1\n",
       "109  1.135144e-39  1.000000e+00     Hoax    Hoax_100\n",
       "110  1.013460e-14  1.000000e+00     Hoax     Hoax_33\n",
       "111  1.045265e-20  1.000000e+00     Hoax     Hoax_24\n",
       "112  1.940402e-23  1.000000e+00     Hoax     Hoax_64\n",
       "113  1.000000e+00  6.231710e-20    NHoax    Nhoax_93\n",
       "114  1.000000e+00  3.324949e-21    NHoax     Nhoax_8\n",
       "115  1.000000e+00  1.779885e-21    NHoax    Nhoax_82\n",
       "116  8.038707e-20  1.000000e+00     Hoax     Hoax_43\n",
       "117  1.000000e+00  4.762504e-23    NHoax    Nhoax_58\n",
       "118  1.000000e+00  7.690934e-24    NHoax    Nhoax_49\n",
       "119  2.445756e-23  1.000000e+00     Hoax     Hoax_41\n",
       "120  5.628392e-44  1.000000e+00     Hoax     Hoax_62\n",
       "121  9.999762e-01  2.377620e-05    NHoax    Nhoax_97\n",
       "122  1.000000e+00  1.333818e-26    NHoax    Nhoax_71\n",
       "123  1.000000e+00  1.179742e-34    NHoax    Nhoax_83\n",
       "124  1.267684e-03  9.987323e-01     Hoax     Hoax_68\n",
       "125  9.999753e-01  2.469286e-05    NHoax    Nhoax_67\n",
       "126  1.000000e+00  1.793353e-17    NHoax    Nhoax_14\n",
       "127  9.633983e-13  1.000000e+00     Hoax     Hoax_81\n",
       "128  8.135698e-17  1.000000e+00     Hoax     Hoax_53\n",
       "129  1.151840e-17  1.000000e+00     Hoax      Hoax_4\n",
       "130  1.000000e+00  2.699633e-15    NHoax    Nhoax_59\n",
       "131  1.000000e+00  5.704802e-37    NHoax    Nhoax_22\n",
       "132  4.629139e-04  9.995371e-01     Hoax     Hoax_57\n",
       "133  1.000000e+00  4.566689e-22    NHoax    Nhoax_18\n",
       "134  1.000000e+00  1.761569e-11    NHoax    Nhoax_13\n",
       "135  3.270085e-24  1.000000e+00     Hoax     Hoax_55\n",
       "136  1.000000e+00  1.272516e-14    NHoax    Nhoax_36\n",
       "137  3.220320e-09  1.000000e+00     Hoax     Hoax_72\n",
       "138  1.000000e+00  8.892243e-12    NHoax     Nhoax_6\n",
       "139  9.999997e-01  2.988360e-07    NHoax    Nhoax_79\n",
       "140  2.241779e-42  1.000000e+00     Hoax     Hoax_97\n",
       "141  2.361427e-21  1.000000e+00     Hoax     Hoax_30\n",
       "142  3.878435e-35  1.000000e+00     Hoax     Hoax_78\n",
       "143  3.501739e-06  9.999965e-01     Hoax     Hoax_94\n",
       "144  1.000000e+00  4.656229e-20    NHoax   Nhoax_100\n",
       "145  1.000000e+00  3.904179e-21    NHoax    Nhoax_95\n",
       "146  1.000000e+00  3.845961e-12    NHoax     Hoax_93\n",
       "147  1.106275e-30  1.000000e+00     Hoax     Hoax_79\n",
       "148  9.999993e-01  7.483021e-07    NHoax    Nhoax_94\n",
       "149  1.000000e+00  7.226192e-19    NHoax    Nhoax_69\n",
       "150  1.569458e-09  1.000000e+00     Hoax     Hoax_52\n",
       "151  1.000000e+00  3.619520e-22    NHoax    Nhoax_65\n",
       "152  1.000000e+00  7.868535e-26    NHoax    Nhoax_78\n",
       "153  1.294651e-09  1.000000e+00     Hoax     Hoax_61\n",
       "154  1.000000e+00  2.014466e-38    NHoax    Nhoax_51\n",
       "155  4.676628e-10  1.000000e+00     Hoax     Hoax_16\n",
       "156  1.000000e+00  2.358074e-21    NHoax    Nhoax_48\n",
       "157  6.380737e-15  1.000000e+00     Hoax     Hoax_40\n",
       "158  1.000000e+00  7.284781e-28    NHoax    Nhoax_43\n",
       "159  2.232953e-15  1.000000e+00     Hoax     Hoax_59\n",
       "160  1.106865e-20  1.000000e+00     Hoax     Hoax_71\n",
       "161  1.000000e+00  2.166109e-25    NHoax    Nhoax_55\n",
       "162  1.000000e+00  1.026599e-15    NHoax    Nhoax_86\n",
       "163  4.773559e-08  1.000000e+00     Hoax     Hoax_73\n",
       "164  3.771685e-13  1.000000e+00     Hoax     Hoax_66\n",
       "165  1.000000e+00  6.622514e-19    NHoax    Nhoax_75\n",
       "166  1.000000e+00  1.844827e-08    NHoax    Nhoax_85\n",
       "167  1.752015e-18  1.000000e+00     Hoax     Hoax_10\n",
       "168  1.000000e+00  2.639639e-21    NHoax    Nhoax_15\n",
       "169  7.466066e-06  9.999925e-01     Hoax     Hoax_15\n",
       "170  9.040638e-13  1.000000e+00     Hoax     Hoax_31\n",
       "171  2.509218e-28  1.000000e+00     Hoax     Hoax_90\n",
       "172  9.631704e-19  1.000000e+00     Hoax     Hoax_98\n",
       "173  1.000000e+00  1.357086e-08    NHoax    Nhoax_24\n",
       "174  9.162767e-29  1.000000e+00     Hoax     Hoax_42\n",
       "175  9.753454e-22  1.000000e+00     Hoax     Hoax_49\n",
       "176  4.549459e-13  1.000000e+00     Hoax     Hoax_96\n",
       "177  4.639152e-16  1.000000e+00     Hoax      Hoax_8\n",
       "178  3.792649e-01  6.207351e-01     Hoax     Hoax_60\n",
       "179  1.055226e-04  9.998945e-01     Hoax     Hoax_84\n",
       "180  3.406629e-13  1.000000e+00     Hoax      Hoax_9\n",
       "181  6.143118e-44  1.000000e+00     Hoax     Hoax_91\n",
       "182  1.000000e+00  1.859308e-10    NHoax    Nhoax_52\n",
       "183  1.000000e+00  4.095878e-13    NHoax    Nhoax_35\n",
       "184  1.000000e+00  2.361690e-16    NHoax    Nhoax_37\n",
       "185  3.175808e-03  9.968242e-01     Hoax     Hoax_17\n",
       "186  1.000000e+00  4.354453e-21    NHoax    Nhoax_21\n",
       "187  1.000000e+00  2.436338e-14    NHoax    Nhoax_81\n",
       "188  1.000000e+00  2.020876e-13    NHoax    Nhoax_40\n",
       "189  1.000000e+00  5.050587e-26    NHoax    Nhoax_80\n",
       "190  1.000000e+00  1.308253e-20    NHoax    Nhoax_77\n",
       "191  4.455330e-04  9.995545e-01     Hoax     Hoax_37\n",
       "192  1.000000e+00  5.438090e-20    NHoax    Nhoax_23\n",
       "193  1.000000e+00  7.280288e-21    NHoax    Nhoax_76\n",
       "194  1.000000e+00  9.516116e-19    NHoax    Nhoax_17\n",
       "195  7.535938e-05  9.999246e-01     Hoax     Hoax_39\n",
       "196  1.000000e+00  9.522595e-22    NHoax    Nhoax_26\n",
       "197  4.427992e-22  1.000000e+00     Hoax     Hoax_46\n",
       "198  9.409464e-10  1.000000e+00     Hoax     Hoax_54\n",
       "199  1.000000e+00  2.846114e-38    NHoax    Nhoax_60"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_prob_mnb = model_mnb.predict_proba(X)\n",
    "pred_mnb = model_mnb.predict(X)\n",
    "mnb_df = pd.DataFrame(data=pred_prob_mnb,index=X.index,columns=['Hoax','NHoax'])\n",
    "mnb_df['Kategori'] = pred_mnb\n",
    "mnb_df['Kategori'] = np.where(mnb_df['Kategori'], 'Hoax', 'NHoax')\n",
    "mnb_df['Kode Berita'] = df['Kode Berita']\n",
    "mnb_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "labels = np.unique(y_test)\n",
    "cm = confusion_matrix(y_test, model_mnb.predict(X_test), labels=labels)\n",
    "sns.heatmap(cm, annot=True, square=True, cmap='Blues', cbar=False, xticklabels=labels, yticklabels=labels,\n",
    "            fmt=\"d\", annot_kws={\"fontsize\": 15})\n",
    "plt.title(f'III. 40 Data Uji: {model_mnb.score(X_test, y_test):.3f}',fontsize=14)\n",
    "plt.xlabel('Prediction', fontsize=14)\n",
    "plt.ylabel('Actual', fontsize=14)\n",
    "plt.yticks(rotation=0, verticalalignment='center');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Uji"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test = pd.read_csv('C:/Users/ASUS/Downloads/Data 80-20.csv', usecols=cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_p2 = X.iloc[199:] # mengambil atribut/fitur data\n",
    "y_p2 = y[199:]\n",
    "teks_p2 = df_test.iloc[199:,2].values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_pred_nb = model_nb.predict(X_p2)\n",
    "new_pred_mnb = model_mnb.predict(X_p2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Berita asli:\n",
      "Seorang ibu rumah tangga bernama Nunki Herwanti di Semarang, kaget karena dinyatakan positif virus Corona. Wanita yang sedang hamil 5 bulan ini tak menyangka karena selama ini ia tidak pernah bepergian jauh baik dalam kota maupun luar negeri.\n",
      "Bahkan, ia juga tak pernah kontak fisik dengan orang-orang yang rawan membawa virus Corona. Lantas darimana dia bisa tertular?\n",
      "Kepada Gubernur Jawa Tengah, Ganjar Pranowo lewat teleconference, Nungki pun menceritakannya kisahnya. \n",
      "\"Tidak ada riwayat perjalanan ke luar kota, saya juga tidak ada riwayat perjalanan ke luar negeri. Bahkan berkerumunan, maksudnya acara yang sangat besar yang berkerumun juga tidak,\" kata Nungki kepada Ganjar beberapa waktu lalu, dikutip dari 20detik.\n",
      "Dia menambahkan bahwa kegiatan sehari-harinya sebelum timbul gejala adalah antar-jemput anak. Serta tidak melakukan kontak fisik dengan siapapun. Namun kegiatan lain yang dia lakukan adalah berkontak dengan tukang sayur keliling langganannya. \n",
      "\n",
      "==================================================================================================== \n",
      "\n",
      "Hasil Prediksi Naive Bayes = NONHOAX\n",
      "1.0\n",
      "==================================================================================================== \n",
      "\n",
      "Hasil Prediksi Multinomial Naive Bayes = NONHOAX\n",
      "1.0\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "print('Berita asli:')\n",
    "print(teks_p2)\n",
    "\n",
    "print(100*'=', '\\n')\n",
    "\n",
    "if new_pred_nb == 1:\n",
    "    print('Hasil Prediksi Naive Bayes = HOAX\\n')\n",
    "else:\n",
    "    print('Hasil Prediksi Naive Bayes = NONHOAX')\n",
    "print(accuracy_score(y_p2, new_pred_nb))\n",
    "\n",
    "print(100*'=', '\\n')\n",
    "\n",
    "if new_pred_mnb == 1:\n",
    "    print('Hasil Prediksi Multinomial Naive Bayes = HOAX')\n",
    "else:\n",
    "    print('Hasil Prediksi Multinomial Naive Bayes = NONHOAX')\n",
    "print(accuracy_score(y_p2, new_pred_mnb))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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