mh-ode-to-code-pred-weather-6th-place-sol.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/jarupula/mh-ode-to-code-pred-weather-6th-place-sol?scriptVersionId=88616025\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown","outputs":[],"execution_count":0},{"cell_type":"markdown","id":"c957855c","metadata":{"papermill":{"duration":0.045773,"end_time":"2022-02-24T05:32:01.927102","exception":false,"start_time":"2022-02-24T05:32:01.881329","status":"completed"},"tags":[]},"source":["# Machine Hack - Ode To Code: Predicting Weather Using Alien Fruit Properties🍊\n","\n","- https://machinehack.com/hackathon/odetocode_predicting_weather_using_alien_fruit_properties/overview"]},{"cell_type":"markdown","id":"aa2d5865","metadata":{"papermill":{"duration":0.044018,"end_time":"2022-02-24T05:32:02.016494","exception":false,"start_time":"2022-02-24T05:32:01.972476","status":"completed"},"tags":[]},"source":["#### Problem Statement:\n","\n","The year is 2050 and a team of astronauts from all over the world went on a mission to an Exoplanet and discovered a vast amount of life and awesome weather. The scientists began collecting data samples of fruits found in their landing site and were curious by their shape and size. They collected data for more than a solar year of the planet to understand the fruit growing conditions in different weathers. \n","\n","To analyze data and grow fruits similar to earth, they began transmitting data back to the Earth, however, due to solar radiation, some data got corrupted and got lost in transmission. Back on Earth, the scientists figured they need to identify the type of climate the exoplanet has based on the properties of the fruit with the existing challenge of missing data. Help the scientists identify the earth-like season in which the fruit must have grown using the data collected."]},{"cell_type":"markdown","id":"0879e5b2","metadata":{"papermill":{"duration":0.043835,"end_time":"2022-02-24T05:32:02.106542","exception":false,"start_time":"2022-02-24T05:32:02.062707","status":"completed"},"tags":[]},"source":["# Importing libraries📚"]},{"cell_type":"code","execution_count":1,"id":"efcc431f","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2022-02-24T05:32:02.202122Z","iopub.status.busy":"2022-02-24T05:32:02.200332Z","iopub.status.idle":"2022-02-24T05:32:07.905622Z","shell.execute_reply":"2022-02-24T05:32:07.904671Z","shell.execute_reply.started":"2022-01-24T08:16:05.737102Z"},"papermill":{"duration":5.75452,"end_time":"2022-02-24T05:32:07.90584","exception":false,"start_time":"2022-02-24T05:32:02.15132","status":"completed"},"tags":[]},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","\n","from sklearn.metrics import accuracy_score\n","from sklearn.preprocessing import OneHotEncoder\n","from sklearn.compose import ColumnTransformer\n","from sklearn.model_selection import train_test_split\n","\n","from tensorflow import keras\n","\n","import warnings\n","warnings.filterwarnings('ignore')\n","pd.set_option('display.max_columns', None)"]},{"cell_type":"markdown","id":"f9be10ba","metadata":{"papermill":{"duration":0.044486,"end_time":"2022-02-24T05:32:07.994992","exception":false,"start_time":"2022-02-24T05:32:07.950506","status":"completed"},"tags":[]},"source":["# Reading data📋"]},{"cell_type":"code","execution_count":2,"id":"770f85ff","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:08.0873Z","iopub.status.busy":"2022-02-24T05:32:08.086624Z","iopub.status.idle":"2022-02-24T05:32:08.22732Z","shell.execute_reply":"2022-02-24T05:32:08.22671Z","shell.execute_reply.started":"2022-01-24T08:16:11.615621Z"},"papermill":{"duration":0.188056,"end_time":"2022-02-24T05:32:08.227471","exception":false,"start_time":"2022-02-24T05:32:08.039415","status":"completed"},"tags":[]},"outputs":[],"source":["train = pd.read_csv('../input/machinehack-ode-to-codedata/train.csv', na_values='')\n","test = pd.read_csv('../input/machinehack-ode-to-codedata/test.csv', na_values='')\n","sample_sub = pd.read_csv('../input/machinehack-ode-to-codedata/sample_submission.csv')"]},{"cell_type":"code","execution_count":3,"id":"f425d1fa","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:08.320441Z","iopub.status.busy":"2022-02-24T05:32:08.319834Z","iopub.status.idle":"2022-02-24T05:32:08.324956Z","shell.execute_reply":"2022-02-24T05:32:08.325545Z","shell.execute_reply.started":"2022-01-24T08:16:11.806666Z"},"papermill":{"duration":0.053101,"end_time":"2022-02-24T05:32:08.325709","exception":false,"start_time":"2022-02-24T05:32:08.272608","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["\n","Train shape: (42748, 14), \n","Test shape: (18321, 14), \n","Sample shape: (18321, 1)\n"]}],"source":["print(f'\\nTrain shape: {train.shape}, \\nTest shape: {test.shape}, \\nSample shape: {sample_sub.shape}')"]},{"cell_type":"code","execution_count":4,"id":"2c0be0b7","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:08.419503Z","iopub.status.busy":"2022-02-24T05:32:08.418867Z","iopub.status.idle":"2022-02-24T05:32:08.445102Z","shell.execute_reply":"2022-02-24T05:32:08.445653Z","shell.execute_reply.started":"2022-01-24T08:16:11.816569Z"},"papermill":{"duration":0.074865,"end_time":"2022-02-24T05:32:08.445862","exception":false,"start_time":"2022-02-24T05:32:08.370997","status":"completed"},"tags":[]},"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>edible-poisonous</th>\n","      <th>cap-diameter</th>\n","      <th>cap-shape</th>\n","      <th>cap-color</th>\n","      <th>does-bruise-or-bleed</th>\n","      <th>gill-attachment</th>\n","      <th>gill-color</th>\n","      <th>stem-height</th>\n","      <th>stem-width</th>\n","      <th>stem-color</th>\n","      <th>has-ring</th>\n","      <th>ring-type</th>\n","      <th>habitat</th>\n","      <th>season</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>p</td>\n","      <td>5.75</td>\n","      <td>x</td>\n","      <td>n</td>\n","      <td>t</td>\n","      <td>s</td>\n","      <td>w</td>\n","      <td>6.13</td>\n","      <td>14.93</td>\n","      <td>w</td>\n","      <td>f</td>\n","      <td>f</td>\n","      <td>d</td>\n","      <td>a</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>p</td>\n","      <td>2.27</td>\n","      <td>o</td>\n","      <td>g</td>\n","      <td>f</td>\n","      <td>f</td>\n","      <td>f</td>\n","      <td>0.00</td>\n","      <td>0.00</td>\n","      <td>f</td>\n","      <td>f</td>\n","      <td>f</td>\n","      <td>d</td>\n","      <td>s</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>p</td>\n","      <td>5.59</td>\n","      <td>c</td>\n","      <td>y</td>\n","      <td>t</td>\n","      <td>x</td>\n","      <td>p</td>\n","      <td>5.47</td>\n","      <td>11.27</td>\n","      <td>w</td>\n","      <td>f</td>\n","      <td>f</td>\n","      <td>d</td>\n","      <td>a</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>p</td>\n","      <td>0.74</td>\n","      <td>x</td>\n","      <td>p</td>\n","      <td>f</td>\n","      <td>a</td>\n","      <td>n</td>\n","      <td>4.33</td>\n","      <td>0.98</td>\n","      <td>k</td>\n","      <td>f</td>\n","      <td>f</td>\n","      <td>d</td>\n","      <td>a</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>p</td>\n","      <td>9.60</td>\n","      <td>x</td>\n","      <td>n</td>\n","      <td>f</td>\n","      <td>a</td>\n","      <td>w</td>\n","      <td>10.84</td>\n","      <td>28.52</td>\n","      <td>w</td>\n","      <td>f</td>\n","      <td>f</td>\n","      <td>d</td>\n","      <td>u</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  edible-poisonous  cap-diameter cap-shape cap-color does-bruise-or-bleed  \\\n","0                p          5.75         x         n                    t   \n","1                p          2.27         o         g                    f   \n","2                p          5.59         c         y                    t   \n","3                p          0.74         x         p                    f   \n","4                p          9.60         x         n                    f   \n","\n","  gill-attachment gill-color  stem-height  stem-width stem-color has-ring  \\\n","0               s          w         6.13       14.93          w        f   \n","1               f          f         0.00        0.00          f        f   \n","2               x          p         5.47       11.27          w        f   \n","3               a          n         4.33        0.98          k        f   \n","4               a          w        10.84       28.52          w        f   \n","\n","  ring-type habitat season  \n","0         f       d      a  \n","1         f       d      s  \n","2         f       d      a  \n","3         f       d      a  \n","4         f       d      u  "]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["train.head()"]},{"cell_type":"markdown","id":"3927144b","metadata":{"papermill":{"duration":0.04544,"end_time":"2022-02-24T05:32:08.536744","exception":false,"start_time":"2022-02-24T05:32:08.491304","status":"completed"},"tags":[]},"source":["#### Missing values counts"]},{"cell_type":"code","execution_count":5,"id":"6317c2b7","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:08.631755Z","iopub.status.busy":"2022-02-24T05:32:08.631108Z","iopub.status.idle":"2022-02-24T05:32:08.691473Z","shell.execute_reply":"2022-02-24T05:32:08.690794Z","shell.execute_reply.started":"2022-01-24T08:16:11.8538Z"},"papermill":{"duration":0.109253,"end_time":"2022-02-24T05:32:08.691617","exception":false,"start_time":"2022-02-24T05:32:08.582364","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["edible-poisonous           0\n","cap-diameter               0\n","cap-shape                  0\n","cap-color                  0\n","does-bruise-or-bleed       0\n","gill-attachment         6940\n","gill-color                 0\n","stem-height                0\n","stem-width                 0\n","stem-color                 0\n","has-ring                   0\n","ring-type               1719\n","habitat                    0\n","season                     0\n","dtype: int64"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["train.isna().sum()"]},{"cell_type":"markdown","id":"05c89d1c","metadata":{"papermill":{"duration":0.045367,"end_time":"2022-02-24T05:32:08.783216","exception":false,"start_time":"2022-02-24T05:32:08.737849","status":"completed"},"tags":[]},"source":["✔ We have missing values in train data in two columns"]},{"cell_type":"code","execution_count":6,"id":"44330fd5","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:08.902045Z","iopub.status.busy":"2022-02-24T05:32:08.880921Z","iopub.status.idle":"2022-02-24T05:32:08.907535Z","shell.execute_reply":"2022-02-24T05:32:08.908044Z","shell.execute_reply.started":"2022-01-24T08:16:11.918409Z"},"papermill":{"duration":0.077541,"end_time":"2022-02-24T05:32:08.908236","exception":false,"start_time":"2022-02-24T05:32:08.830695","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["edible-poisonous            0\n","cap-diameter                0\n","cap-shape                   0\n","cap-color                   0\n","does-bruise-or-bleed        0\n","gill-attachment          2944\n","gill-color                  0\n","stem-height                 0\n","stem-width                  0\n","stem-color                  0\n","has-ring                    0\n","ring-type                 752\n","habitat                     0\n","season                  18321\n","dtype: int64"]},"execution_count":6,"metadata":{},"output_type":"execute_result"}],"source":["test.isna().sum()"]},{"cell_type":"markdown","id":"d0e6204b","metadata":{"papermill":{"duration":0.046156,"end_time":"2022-02-24T05:32:09.001747","exception":false,"start_time":"2022-02-24T05:32:08.955591","status":"completed"},"tags":[]},"source":["✔ Same columns are missing in both train and test\n","\n","✔ Missing ratio(~) is preserved in train and test"]},{"cell_type":"code","execution_count":7,"id":"096e344f","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:09.104596Z","iopub.status.busy":"2022-02-24T05:32:09.096926Z","iopub.status.idle":"2022-02-24T05:32:09.134498Z","shell.execute_reply":"2022-02-24T05:32:09.133924Z","shell.execute_reply.started":"2022-01-24T08:16:11.951252Z"},"papermill":{"duration":0.086752,"end_time":"2022-02-24T05:32:09.134645","exception":false,"start_time":"2022-02-24T05:32:09.047893","status":"completed"},"tags":[]},"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>cap-diameter</th>\n","      <th>stem-height</th>\n","      <th>stem-width</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>42748.000000</td>\n","      <td>42748.000000</td>\n","      <td>42748.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>6.712018</td>\n","      <td>6.580449</td>\n","      <td>12.133964</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>5.203768</td>\n","      <td>3.368385</td>\n","      <td>10.058929</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>0.380000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>3.480000</td>\n","      <td>4.640000</td>\n","      <td>5.190000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>5.840000</td>\n","      <td>5.950000</td>\n","      <td>10.140000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>8.540000</td>\n","      <td>7.740000</td>\n","      <td>16.530000</td>\n","    </tr>\n","    <tr>\n","      <th>80%</th>\n","      <td>9.310000</td>\n","      <td>8.300000</td>\n","      <td>17.940000</td>\n","    </tr>\n","    <tr>\n","      <th>90%</th>\n","      <td>11.893000</td>\n","      <td>10.430000</td>\n","      <td>24.403000</td>\n","    </tr>\n","    <tr>\n","      <th>95%</th>\n","      <td>15.070000</td>\n","      <td>12.550000</td>\n","      <td>30.016500</td>\n","    </tr>\n","    <tr>\n","      <th>99%</th>\n","      <td>21.310000</td>\n","      <td>18.825300</td>\n","      <td>48.805300</td>\n","    </tr>\n","    <tr>\n","      <th>99.9%</th>\n","      <td>53.752770</td>\n","      <td>28.008190</td>\n","      <td>80.135780</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>62.340000</td>\n","      <td>33.920000</td>\n","      <td>103.910000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["       cap-diameter   stem-height    stem-width\n","count  42748.000000  42748.000000  42748.000000\n","mean       6.712018      6.580449     12.133964\n","std        5.203768      3.368385     10.058929\n","min        0.380000      0.000000      0.000000\n","25%        3.480000      4.640000      5.190000\n","50%        5.840000      5.950000     10.140000\n","75%        8.540000      7.740000     16.530000\n","80%        9.310000      8.300000     17.940000\n","90%       11.893000     10.430000     24.403000\n","95%       15.070000     12.550000     30.016500\n","99%       21.310000     18.825300     48.805300\n","99.9%     53.752770     28.008190     80.135780\n","max       62.340000     33.920000    103.910000"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["train.describe(percentiles=[0.25, 0.5, 0.75, 0.8, 0.9, 0.95, 0.99, 0.999])"]},{"cell_type":"code","execution_count":8,"id":"82efb197","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:09.24202Z","iopub.status.busy":"2022-02-24T05:32:09.232166Z","iopub.status.idle":"2022-02-24T05:32:09.244668Z","shell.execute_reply":"2022-02-24T05:32:09.245213Z","shell.execute_reply.started":"2022-01-24T08:16:11.996483Z"},"papermill":{"duration":0.062953,"end_time":"2022-02-24T05:32:09.245384","exception":false,"start_time":"2022-02-24T05:32:09.182431","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["a    21103\n","u    16055\n","w     3698\n","s     1892\n","Name: season, dtype: int64"]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["train.season.value_counts(dropna=False)"]},{"cell_type":"markdown","id":"7d3c33db","metadata":{"papermill":{"duration":0.049203,"end_time":"2022-02-24T05:32:09.34308","exception":false,"start_time":"2022-02-24T05:32:09.293877","status":"completed"},"tags":[]},"source":["# Pre-Processing 🛠"]},{"cell_type":"code","execution_count":9,"id":"e3ab0a86","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:09.447436Z","iopub.status.busy":"2022-02-24T05:32:09.443012Z","iopub.status.idle":"2022-02-24T05:32:09.450128Z","shell.execute_reply":"2022-02-24T05:32:09.450649Z","shell.execute_reply.started":"2022-01-24T08:16:12.012323Z"},"papermill":{"duration":0.060454,"end_time":"2022-02-24T05:32:09.450858","exception":false,"start_time":"2022-02-24T05:32:09.390404","status":"completed"},"tags":[]},"outputs":[],"source":["def map_bool_cols(df):\n","    e_p = {'p': 1, 'e': 0}\n","    b_b = {'t': 1, 'f': 0}\n","    h_r = {'t': 1, 'f': 0}\n","    \n","    df['edible-poisonous'] = df['edible-poisonous'].map(e_p)\n","    df['does-bruise-or-bleed'] = df['does-bruise-or-bleed'].map(b_b)\n","    df['has-ring'] = df['has-ring'].map(h_r)\n","    \n","    return df"]},{"cell_type":"code","execution_count":10,"id":"9a34856b","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:09.548733Z","iopub.status.busy":"2022-02-24T05:32:09.548093Z","iopub.status.idle":"2022-02-24T05:32:09.588801Z","shell.execute_reply":"2022-02-24T05:32:09.589354Z","shell.execute_reply.started":"2022-01-24T08:16:12.02406Z"},"papermill":{"duration":0.091233,"end_time":"2022-02-24T05:32:09.589529","exception":false,"start_time":"2022-02-24T05:32:09.498296","status":"completed"},"tags":[]},"outputs":[],"source":["train = map_bool_cols(train)\n","test = map_bool_cols(test)"]},{"cell_type":"code","execution_count":11,"id":"a968aa11","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:09.686598Z","iopub.status.busy":"2022-02-24T05:32:09.685999Z","iopub.status.idle":"2022-02-24T05:32:09.689552Z","shell.execute_reply":"2022-02-24T05:32:09.690096Z","shell.execute_reply.started":"2022-01-24T08:16:12.07869Z"},"papermill":{"duration":0.053697,"end_time":"2022-02-24T05:32:09.690268","exception":false,"start_time":"2022-02-24T05:32:09.636571","status":"completed"},"tags":[]},"outputs":[],"source":["num_cols = ['edible-poisonous','cap-diameter','does-bruise-or-bleed','stem-height',\n","            'stem-width','has-ring']\n","cat_cols = ['cap-shape', 'cap-color', 'gill-color', 'stem-color', 'habitat']"]},{"cell_type":"markdown","id":"eddb488b","metadata":{"papermill":{"duration":0.047297,"end_time":"2022-02-24T05:32:09.7846","exception":false,"start_time":"2022-02-24T05:32:09.737303","status":"completed"},"tags":[]},"source":["## Imputing missing values\n","\n","#### gill-attachment"]},{"cell_type":"markdown","id":"bc8d91b8","metadata":{"papermill":{"duration":0.047362,"end_time":"2022-02-24T05:32:09.880377","exception":false,"start_time":"2022-02-24T05:32:09.833015","status":"completed"},"tags":[]},"source":["#### Missing values are predicted using a simple NN instead of using simple impute methods"]},{"cell_type":"code","execution_count":12,"id":"2503c0a9","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:09.977836Z","iopub.status.busy":"2022-02-24T05:32:09.977116Z","iopub.status.idle":"2022-02-24T05:32:10.012559Z","shell.execute_reply":"2022-02-24T05:32:10.013098Z","shell.execute_reply.started":"2022-01-24T08:16:12.085951Z"},"papermill":{"duration":0.085704,"end_time":"2022-02-24T05:32:10.013291","exception":false,"start_time":"2022-02-24T05:32:09.927587","status":"completed"},"tags":[]},"outputs":[],"source":["temp_gill = train.drop(['ring-type', 'season'], axis=1).copy()\n","train_gill = temp_gill[temp_gill['gill-attachment'].fillna(0) != 0] #non-missing value rows\n","test_gill = temp_gill[temp_gill['gill-attachment'].isna()] # missing value rows\n","test_gill_indexes = test_gill.index"]},{"cell_type":"markdown","id":"a5b1f05b","metadata":{"papermill":{"duration":0.046704,"end_time":"2022-02-24T05:32:10.107649","exception":false,"start_time":"2022-02-24T05:32:10.060945","status":"completed"},"tags":[]},"source":["trainsforming categorical columns and not changing numerical columns"]},{"cell_type":"code","execution_count":13,"id":"d1009f56","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:10.204794Z","iopub.status.busy":"2022-02-24T05:32:10.204127Z","iopub.status.idle":"2022-02-24T05:32:10.208031Z","shell.execute_reply":"2022-02-24T05:32:10.208545Z","shell.execute_reply.started":"2022-01-24T08:16:12.130206Z"},"papermill":{"duration":0.054202,"end_time":"2022-02-24T05:32:10.208742","exception":false,"start_time":"2022-02-24T05:32:10.15454","status":"completed"},"tags":[]},"outputs":[],"source":["featurization_gill = ColumnTransformer(transformers=[\n","    ('one_hot_gill_x', OneHotEncoder(), cat_cols), # OHE categorical columns\n","    ('num_pass', 'passthrough', num_cols) # Don't transform numerical columns\n","])"]},{"cell_type":"code","execution_count":14,"id":"4ddcc26e","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:10.309834Z","iopub.status.busy":"2022-02-24T05:32:10.309111Z","iopub.status.idle":"2022-02-24T05:32:11.604171Z","shell.execute_reply":"2022-02-24T05:32:11.604962Z","shell.execute_reply.started":"2022-01-24T08:16:12.135199Z"},"papermill":{"duration":1.349299,"end_time":"2022-02-24T05:32:11.605187","exception":false,"start_time":"2022-02-24T05:32:10.255888","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["\n","User settings:\n","\n","   KMP_AFFINITY=granularity=fine,verbose,compact,1,0\n","   KMP_BLOCKTIME=0\n","   KMP_DUPLICATE_LIB_OK=True\n","   KMP_INIT_AT_FORK=FALSE\n","   KMP_SETTINGS=1\n","   KMP_WARNINGS=0\n","\n","Effective settings:\n","\n","   KMP_ABORT_DELAY=0\n","   KMP_ADAPTIVE_LOCK_PROPS='1,1024'\n","   KMP_ALIGN_ALLOC=64\n","   KMP_ALL_THREADPRIVATE=128\n","   KMP_ATOMIC_MODE=2\n","   KMP_BLOCKTIME=0\n","   KMP_CPUINFO_FILE: value is not defined\n","   KMP_DETERMINISTIC_REDUCTION=false\n","   KMP_DEVICE_THREAD_LIMIT=2147483647\n","   KMP_DISP_NUM_BUFFERS=7\n","   KMP_DUPLICATE_LIB_OK=true\n","   KMP_ENABLE_TASK_THROTTLING=true\n","   KMP_FORCE_REDUCTION: value is not defined\n","   KMP_FOREIGN_THREADS_THREADPRIVATE=true\n","   KMP_FORKJOIN_BARRIER='2,2'\n","   KMP_FORKJOIN_BARRIER_PATTERN='hyper,hyper'\n","   KMP_GTID_MODE=3\n","   KMP_HANDLE_SIGNALS=false\n","   KMP_HOT_TEAMS_MAX_LEVEL=1\n","   KMP_HOT_TEAMS_MODE=0\n","   KMP_INIT_AT_FORK=true\n","   KMP_LIBRARY=throughput\n","   KMP_LOCK_KIND=queuing\n","   KMP_MALLOC_POOL_INCR=1M\n","   KMP_NUM_LOCKS_IN_BLOCK=1\n","   KMP_PLAIN_BARRIER='2,2'\n","   KMP_PLAIN_BARRIER_PATTERN='hyper,hyper'\n","   KMP_REDUCTION_BARRIER='1,1'\n","   KMP_REDUCTION_BARRIER_PATTERN='hyper,hyper'\n","   KMP_SCHEDULE='static,balanced;guided,iterative'\n","   KMP_SETTINGS=true\n","   KMP_SPIN_BACKOFF_PARAMS='4096,100'\n","   KMP_STACKOFFSET=64\n","   KMP_STACKPAD=0\n","   KMP_STACKSIZE=8M\n","   KMP_STORAGE_MAP=false\n","   KMP_TASKING=2\n","   KMP_TASKLOOP_MIN_TASKS=0\n","   KMP_TASK_STEALING_CONSTRAINT=1\n","   KMP_TEAMS_THREAD_LIMIT=4\n","   KMP_TOPOLOGY_METHOD=all\n","   KMP_USE_YIELD=1\n","   KMP_VERSION=false\n","   KMP_WARNINGS=false\n","   OMP_AFFINITY_FORMAT='OMP: pid %P tid %i thread %n bound to OS proc set {%A}'\n","   OMP_ALLOCATOR=omp_default_mem_alloc\n","   OMP_CANCELLATION=false\n","   OMP_DEFAULT_DEVICE=0\n","   OMP_DISPLAY_AFFINITY=false\n","   OMP_DISPLAY_ENV=false\n","   OMP_DYNAMIC=false\n","   OMP_MAX_ACTIVE_LEVELS=1\n","   OMP_MAX_TASK_PRIORITY=0\n","   OMP_NESTED: deprecated; max-active-levels-var=1\n","   OMP_NUM_THREADS: value is not defined\n","   OMP_PLACES: value is not defined\n","   OMP_PROC_BIND='intel'\n","   OMP_SCHEDULE='static'\n","   OMP_STACKSIZE=8M\n","   OMP_TARGET_OFFLOAD=DEFAULT\n","   OMP_THREAD_LIMIT=2147483647\n","   OMP_WAIT_POLICY=PASSIVE\n","   KMP_AFFINITY='verbose,warnings,respect,granularity=fine,compact,1,0'\n","\n","2022-02-24 05:32:11.528228: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.\n"]}],"source":["X_gill = featurization_gill.fit_transform(train_gill.drop('gill-attachment', axis=1))\n","one_hot_gill_y = OneHotEncoder()\n","y_gill = one_hot_gill_y.fit_transform(np.array(train_gill['gill-attachment']).reshape(-1, 1))\n","\n","X_gill_train, X_gill_val, y_gill_train, y_gill_val = train_test_split(X_gill, y_gill, \n","                                                                      random_state=42)\n","\n","model_gill = keras.models.Sequential([\n","    keras.layers.Input(shape=X_gill.shape[1]),\n","    keras.layers.Dense(64, activation='relu'),\n","    keras.layers.Dense(32, activation='relu'),\n","    keras.layers.Dense(7, activation='softmax')\n","])\n","model_gill.compile('adam', loss='categorical_crossentropy')"]},{"cell_type":"code","execution_count":15,"id":"90801c70","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:11.707669Z","iopub.status.busy":"2022-02-24T05:32:11.706842Z","iopub.status.idle":"2022-02-24T05:32:11.710071Z","shell.execute_reply":"2022-02-24T05:32:11.710596Z","shell.execute_reply.started":"2022-01-24T08:16:13.569982Z"},"papermill":{"duration":0.056848,"end_time":"2022-02-24T05:32:11.710774","exception":false,"start_time":"2022-02-24T05:32:11.653926","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: \"sequential\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","dense (Dense)                (None, 64)                3776      \n","_________________________________________________________________\n","dense_1 (Dense)              (None, 32)                2080      \n","_________________________________________________________________\n","dense_2 (Dense)              (None, 7)                 231       \n","=================================================================\n","Total params: 6,087\n","Trainable params: 6,087\n","Non-trainable params: 0\n","_________________________________________________________________\n"]}],"source":["model_gill.summary()"]},{"cell_type":"code","execution_count":16,"id":"e6edff2f","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:11.812237Z","iopub.status.busy":"2022-02-24T05:32:11.811199Z","iopub.status.idle":"2022-02-24T05:32:32.231664Z","shell.execute_reply":"2022-02-24T05:32:32.230759Z","shell.execute_reply.started":"2022-01-24T08:16:13.580921Z"},"papermill":{"duration":20.471769,"end_time":"2022-02-24T05:32:32.231838","exception":false,"start_time":"2022-02-24T05:32:11.760069","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["2022-02-24 05:32:11.920956: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n"]},{"name":"stdout","output_type":"stream","text":["Epoch 1/10\n","840/840 [==============================] - 3s 2ms/step - loss: 0.8682 - val_loss: 0.4982\n","Epoch 2/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.3769 - val_loss: 0.2879\n","Epoch 3/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.2433 - val_loss: 0.2026\n","Epoch 4/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.1730 - val_loss: 0.1526\n","Epoch 5/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.1330 - val_loss: 0.1367\n","Epoch 6/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.1090 - val_loss: 0.1022\n","Epoch 7/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.0976 - val_loss: 0.0920\n","Epoch 8/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.0849 - val_loss: 0.0862\n","Epoch 9/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.0770 - val_loss: 0.0729\n","Epoch 10/10\n","840/840 [==============================] - 2s 2ms/step - loss: 0.0772 - val_loss: 0.0827\n"]}],"source":["history = model_gill.fit(X_gill_train.toarray(), y_gill_train.toarray(), \n","                         validation_data=(X_gill_val.toarray(), y_gill_val.toarray()), epochs=10)"]},{"cell_type":"code","execution_count":17,"id":"aa674118","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:32.536425Z","iopub.status.busy":"2022-02-24T05:32:32.535799Z","iopub.status.idle":"2022-02-24T05:32:32.975341Z","shell.execute_reply":"2022-02-24T05:32:32.974595Z","shell.execute_reply.started":"2022-01-24T08:16:55.152529Z"},"papermill":{"duration":0.592027,"end_time":"2022-02-24T05:32:32.975486","exception":false,"start_time":"2022-02-24T05:32:32.383459","status":"completed"},"tags":[]},"outputs":[],"source":["preds = model_gill.predict(featurization_gill.transform(test_gill))"]},{"cell_type":"code","execution_count":18,"id":"ae9db2f3","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:33.277231Z","iopub.status.busy":"2022-02-24T05:32:33.276227Z","iopub.status.idle":"2022-02-24T05:32:38.546008Z","shell.execute_reply":"2022-02-24T05:32:38.545375Z","shell.execute_reply.started":"2022-01-24T08:16:55.638135Z"},"papermill":{"duration":5.421546,"end_time":"2022-02-24T05:32:38.546153","exception":false,"start_time":"2022-02-24T05:32:33.124607","status":"completed"},"tags":[]},"outputs":[],"source":["for i, idx in enumerate(test_gill_indexes):\n","    train.loc[idx, 'gill-attachment'] = one_hot_gill_y.inverse_transform(np.array(preds[i]).reshape(1, -1))[0][0]"]},{"cell_type":"code","execution_count":19,"id":"b5ffbe74","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:38.84684Z","iopub.status.busy":"2022-02-24T05:32:38.845795Z","iopub.status.idle":"2022-02-24T05:32:38.855474Z","shell.execute_reply":"2022-02-24T05:32:38.855972Z","shell.execute_reply.started":"2022-01-24T08:17:00.769828Z"},"papermill":{"duration":0.161831,"end_time":"2022-02-24T05:32:38.856158","exception":false,"start_time":"2022-02-24T05:32:38.694327","status":"completed"},"tags":[]},"outputs":[],"source":["test_gill_df = test[test['gill-attachment'].isna()].drop(['ring-type', 'season'], axis=1).copy()\n","test_gill_indexes_df = test_gill_df.index"]},{"cell_type":"code","execution_count":20,"id":"525af5f1","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:39.167942Z","iopub.status.busy":"2022-02-24T05:32:39.156928Z","iopub.status.idle":"2022-02-24T05:32:39.298986Z","shell.execute_reply":"2022-02-24T05:32:39.297898Z","shell.execute_reply.started":"2022-01-24T08:17:00.781972Z"},"papermill":{"duration":0.294604,"end_time":"2022-02-24T05:32:39.299163","exception":false,"start_time":"2022-02-24T05:32:39.004559","status":"completed"},"tags":[]},"outputs":[],"source":["test_preds_gill = model_gill.predict(featurization_gill.transform(test_gill_df))"]},{"cell_type":"code","execution_count":21,"id":"bf3ac0b9","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:39.615021Z","iopub.status.busy":"2022-02-24T05:32:39.614296Z","iopub.status.idle":"2022-02-24T05:32:41.149838Z","shell.execute_reply":"2022-02-24T05:32:41.150367Z","shell.execute_reply.started":"2022-01-24T08:17:00.996206Z"},"papermill":{"duration":1.695499,"end_time":"2022-02-24T05:32:41.150564","exception":false,"start_time":"2022-02-24T05:32:39.455065","status":"completed"},"tags":[]},"outputs":[],"source":["# Transforming test set\n","for i, idx in enumerate(test_gill_indexes_df):\n","    test.loc[idx, 'gill-attachment'] = one_hot_gill_y.inverse_transform(\n","        np.array(test_preds_gill[i]).reshape(1, -1))[0][0] "]},{"cell_type":"markdown","id":"095df3c7","metadata":{"papermill":{"duration":0.148543,"end_time":"2022-02-24T05:32:41.447625","exception":false,"start_time":"2022-02-24T05:32:41.299082","status":"completed"},"tags":[]},"source":["### ring-type"]},{"cell_type":"code","execution_count":22,"id":"fcf156c8","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:41.754013Z","iopub.status.busy":"2022-02-24T05:32:41.752638Z","iopub.status.idle":"2022-02-24T05:32:41.785793Z","shell.execute_reply":"2022-02-24T05:32:41.785228Z","shell.execute_reply.started":"2022-01-24T08:17:02.562401Z"},"papermill":{"duration":0.189505,"end_time":"2022-02-24T05:32:41.785949","exception":false,"start_time":"2022-02-24T05:32:41.596444","status":"completed"},"tags":[]},"outputs":[],"source":["temp_ring = train.drop(['gill-attachment', 'season'], axis=1).copy()\n","train_ring = temp_ring[temp_ring['ring-type'].fillna(0) != 0] # Non-missing value rows\n","test_ring = temp_ring[temp_ring['ring-type'].isna()] # Missing value rows\n","test_ring_indexes = test_ring.index"]},{"cell_type":"code","execution_count":23,"id":"65feccfd","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:42.091047Z","iopub.status.busy":"2022-02-24T05:32:42.089977Z","iopub.status.idle":"2022-02-24T05:32:42.091984Z","shell.execute_reply":"2022-02-24T05:32:42.092471Z","shell.execute_reply.started":"2022-01-24T08:17:02.602684Z"},"papermill":{"duration":0.156723,"end_time":"2022-02-24T05:32:42.092643","exception":false,"start_time":"2022-02-24T05:32:41.93592","status":"completed"},"tags":[]},"outputs":[],"source":["featurization_ring = ColumnTransformer(transformers=[\n","    ('one_hot_ring_x', OneHotEncoder(), cat_cols),\n","    ('num_pass', 'passthrough', num_cols)\n","])"]},{"cell_type":"code","execution_count":24,"id":"6b75bcf1","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:42.405227Z","iopub.status.busy":"2022-02-24T05:32:42.404134Z","iopub.status.idle":"2022-02-24T05:32:42.593518Z","shell.execute_reply":"2022-02-24T05:32:42.592907Z","shell.execute_reply.started":"2022-01-24T08:17:02.610134Z"},"papermill":{"duration":0.351036,"end_time":"2022-02-24T05:32:42.593676","exception":false,"start_time":"2022-02-24T05:32:42.24264","status":"completed"},"tags":[]},"outputs":[],"source":["X_ring = featurization_ring.fit_transform(train_ring.drop('ring-type', axis=1))\n","one_hot_ring_y = OneHotEncoder()\n","y_ring = one_hot_ring_y.fit_transform(np.array(train_ring['ring-type']).reshape(-1, 1))\n","\n","X_ring_train, X_ring_val, y_ring_train, y_ring_val = train_test_split(X_ring, y_ring, \n","                                                                      random_state=42)\n","\n","model_ring = keras.models.Sequential([\n","    keras.layers.Input(shape=X_ring.shape[1]),\n","    keras.layers.Dense(64, activation='relu'),\n","    keras.layers.Dense(32, activation='relu'),\n","    keras.layers.Dense(8, activation='softmax')\n","])\n","model_ring.compile('adam', loss='categorical_crossentropy')"]},{"cell_type":"code","execution_count":25,"id":"b32c5f5f","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:42.897272Z","iopub.status.busy":"2022-02-24T05:32:42.896538Z","iopub.status.idle":"2022-02-24T05:32:42.903405Z","shell.execute_reply":"2022-02-24T05:32:42.904126Z","shell.execute_reply.started":"2022-01-24T08:17:02.813098Z"},"papermill":{"duration":0.16044,"end_time":"2022-02-24T05:32:42.904357","exception":false,"start_time":"2022-02-24T05:32:42.743917","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: \"sequential_1\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","dense_3 (Dense)              (None, 64)                3776      \n","_________________________________________________________________\n","dense_4 (Dense)              (None, 32)                2080      \n","_________________________________________________________________\n","dense_5 (Dense)              (None, 8)                 264       \n","=================================================================\n","Total params: 6,120\n","Trainable params: 6,120\n","Non-trainable params: 0\n","_________________________________________________________________\n"]}],"source":["model_ring.summary()"]},{"cell_type":"code","execution_count":26,"id":"67a5b8cf","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:32:43.206497Z","iopub.status.busy":"2022-02-24T05:32:43.20588Z","iopub.status.idle":"2022-02-24T05:33:04.968468Z","shell.execute_reply":"2022-02-24T05:33:04.969097Z","shell.execute_reply.started":"2022-01-24T08:17:02.823699Z"},"papermill":{"duration":21.915394,"end_time":"2022-02-24T05:33:04.969282","exception":false,"start_time":"2022-02-24T05:32:43.053888","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Epoch 1/10\n","962/962 [==============================] - 3s 2ms/step - loss: 0.2927 - val_loss: 0.0895\n","Epoch 2/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0629 - val_loss: 0.0525\n","Epoch 3/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0449 - val_loss: 0.0435\n","Epoch 4/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0400 - val_loss: 0.0407\n","Epoch 5/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0373 - val_loss: 0.0439\n","Epoch 6/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0369 - val_loss: 0.0370\n","Epoch 7/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0344 - val_loss: 0.0384\n","Epoch 8/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0336 - val_loss: 0.0470\n","Epoch 9/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0334 - val_loss: 0.0331\n","Epoch 10/10\n","962/962 [==============================] - 2s 2ms/step - loss: 0.0327 - val_loss: 0.0342\n"]}],"source":["history_ring = model_ring.fit(X_ring_train.toarray(), y_ring_train.toarray(), \n","                         validation_data=(X_ring_val.toarray(), y_ring_val.toarray()), epochs=10)"]},{"cell_type":"code","execution_count":27,"id":"2b156d6b","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:05.488496Z","iopub.status.busy":"2022-02-24T05:33:05.486081Z","iopub.status.idle":"2022-02-24T05:33:05.658188Z","shell.execute_reply":"2022-02-24T05:33:05.65876Z","shell.execute_reply.started":"2022-01-24T08:17:31.909822Z"},"papermill":{"duration":0.43124,"end_time":"2022-02-24T05:33:05.65894","exception":false,"start_time":"2022-02-24T05:33:05.2277","status":"completed"},"tags":[]},"outputs":[],"source":["preds_ring = model_ring.predict(featurization_ring.transform(test_ring))"]},{"cell_type":"code","execution_count":28,"id":"0d82a611","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:06.177098Z","iopub.status.busy":"2022-02-24T05:33:06.176096Z","iopub.status.idle":"2022-02-24T05:33:07.681975Z","shell.execute_reply":"2022-02-24T05:33:07.681188Z","shell.execute_reply.started":"2022-01-24T08:17:32.098301Z"},"papermill":{"duration":1.764553,"end_time":"2022-02-24T05:33:07.68213","exception":false,"start_time":"2022-02-24T05:33:05.917577","status":"completed"},"tags":[]},"outputs":[],"source":["for i, idx in enumerate(test_ring_indexes):\n","    train.loc[idx, 'ring-type'] = one_hot_ring_y.inverse_transform(np.array(preds_ring[i]).reshape(1, -1))[0][0]"]},{"cell_type":"code","execution_count":29,"id":"606c1257","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:08.216462Z","iopub.status.busy":"2022-02-24T05:33:08.215235Z","iopub.status.idle":"2022-02-24T05:33:08.220848Z","shell.execute_reply":"2022-02-24T05:33:08.220301Z","shell.execute_reply.started":"2022-01-24T08:17:33.542217Z"},"papermill":{"duration":0.271709,"end_time":"2022-02-24T05:33:08.221","exception":false,"start_time":"2022-02-24T05:33:07.949291","status":"completed"},"tags":[]},"outputs":[],"source":["test_ring_df = test[test['ring-type'].isna()].drop(['gill-attachment', 'season'], axis=1).copy()\n","test_ring_indexes_df = test_ring_df.index"]},{"cell_type":"code","execution_count":30,"id":"b39366cc","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:08.740457Z","iopub.status.busy":"2022-02-24T05:33:08.739793Z","iopub.status.idle":"2022-02-24T05:33:08.785625Z","shell.execute_reply":"2022-02-24T05:33:08.786202Z","shell.execute_reply.started":"2022-01-24T08:17:33.553543Z"},"papermill":{"duration":0.309485,"end_time":"2022-02-24T05:33:08.786387","exception":false,"start_time":"2022-02-24T05:33:08.476902","status":"completed"},"tags":[]},"outputs":[],"source":["test_preds_ring = model_ring.predict(featurization_ring.transform(test_ring_df))"]},{"cell_type":"code","execution_count":31,"id":"dd015999","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:09.392025Z","iopub.status.busy":"2022-02-24T05:33:09.390958Z","iopub.status.idle":"2022-02-24T05:33:09.837037Z","shell.execute_reply":"2022-02-24T05:33:09.837622Z","shell.execute_reply.started":"2022-01-24T08:17:33.615598Z"},"papermill":{"duration":0.768572,"end_time":"2022-02-24T05:33:09.837858","exception":false,"start_time":"2022-02-24T05:33:09.069286","status":"completed"},"tags":[]},"outputs":[],"source":["for i, idx in enumerate(test_ring_indexes_df):\n","    test.loc[idx, 'ring-type'] = one_hot_ring_y.inverse_transform(\n","        np.array(test_preds_ring[i]).reshape(1, -1))[0][0]"]},{"cell_type":"code","execution_count":32,"id":"d72f0907","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:10.395166Z","iopub.status.busy":"2022-02-24T05:33:10.355311Z","iopub.status.idle":"2022-02-24T05:33:10.403106Z","shell.execute_reply":"2022-02-24T05:33:10.403547Z","shell.execute_reply.started":"2022-01-24T08:17:34.076884Z"},"papermill":{"duration":0.306718,"end_time":"2022-02-24T05:33:10.403737","exception":false,"start_time":"2022-02-24T05:33:10.097019","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["edible-poisonous        0\n","cap-diameter            0\n","cap-shape               0\n","cap-color               0\n","does-bruise-or-bleed    0\n","gill-attachment         0\n","gill-color              0\n","stem-height             0\n","stem-width              0\n","stem-color              0\n","has-ring                0\n","ring-type               0\n","habitat                 0\n","season                  0\n","dtype: int64"]},"execution_count":32,"metadata":{},"output_type":"execute_result"}],"source":["train.isna().sum()"]},{"cell_type":"code","execution_count":33,"id":"4cc218c7","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:10.922179Z","iopub.status.busy":"2022-02-24T05:33:10.92116Z","iopub.status.idle":"2022-02-24T05:33:10.943535Z","shell.execute_reply":"2022-02-24T05:33:10.944185Z","shell.execute_reply.started":"2022-01-24T08:17:34.123637Z"},"papermill":{"duration":0.284788,"end_time":"2022-02-24T05:33:10.94438","exception":false,"start_time":"2022-02-24T05:33:10.659592","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["edible-poisonous            0\n","cap-diameter                0\n","cap-shape                   0\n","cap-color                   0\n","does-bruise-or-bleed        0\n","gill-attachment             0\n","gill-color                  0\n","stem-height                 0\n","stem-width                  0\n","stem-color                  0\n","has-ring                    0\n","ring-type                   0\n","habitat                     0\n","season                  18321\n","dtype: int64"]},"execution_count":33,"metadata":{},"output_type":"execute_result"}],"source":["test.isna().sum()"]},{"cell_type":"markdown","id":"d74a3e97","metadata":{"papermill":{"duration":0.319094,"end_time":"2022-02-24T05:33:11.584015","exception":false,"start_time":"2022-02-24T05:33:11.264921","status":"completed"},"tags":[]},"source":["# Training🏋️‍♂️"]},{"cell_type":"code","execution_count":34,"id":"ff680fc3","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:12.14399Z","iopub.status.busy":"2022-02-24T05:33:12.143295Z","iopub.status.idle":"2022-02-24T05:33:12.15297Z","shell.execute_reply":"2022-02-24T05:33:12.153486Z","shell.execute_reply.started":"2022-01-24T08:17:34.152719Z"},"papermill":{"duration":0.271694,"end_time":"2022-02-24T05:33:12.153655","exception":false,"start_time":"2022-02-24T05:33:11.881961","status":"completed"},"tags":[]},"outputs":[],"source":["num_cols_final = train.select_dtypes(include=['int64', 'float64']).columns\n","cat_cols_final = train.select_dtypes(include=['object']).columns[:-1]"]},{"cell_type":"code","execution_count":35,"id":"5c5fe281","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:12.669319Z","iopub.status.busy":"2022-02-24T05:33:12.668616Z","iopub.status.idle":"2022-02-24T05:33:12.672927Z","shell.execute_reply":"2022-02-24T05:33:12.673379Z","shell.execute_reply.started":"2022-01-24T08:17:34.169987Z"},"papermill":{"duration":0.263851,"end_time":"2022-02-24T05:33:12.673545","exception":false,"start_time":"2022-02-24T05:33:12.409694","status":"completed"},"tags":[]},"outputs":[],"source":["featurization = ColumnTransformer(transformers=[\n","    ('final_onehot', OneHotEncoder(), cat_cols_final),\n","    ('final_num', 'passthrough', num_cols_final)\n","])"]},{"cell_type":"code","execution_count":36,"id":"94d47e07","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:13.194347Z","iopub.status.busy":"2022-02-24T05:33:13.193608Z","iopub.status.idle":"2022-02-24T05:33:13.196542Z","shell.execute_reply":"2022-02-24T05:33:13.197186Z","shell.execute_reply.started":"2022-01-24T08:17:34.177164Z"},"papermill":{"duration":0.26517,"end_time":"2022-02-24T05:33:13.197363","exception":false,"start_time":"2022-02-24T05:33:12.932193","status":"completed"},"tags":[]},"outputs":[],"source":["one_hot_final = OneHotEncoder()"]},{"cell_type":"code","execution_count":37,"id":"6c719c75","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:13.711559Z","iopub.status.busy":"2022-02-24T05:33:13.710876Z","iopub.status.idle":"2022-02-24T05:33:13.976255Z","shell.execute_reply":"2022-02-24T05:33:13.976859Z","shell.execute_reply.started":"2022-01-24T08:17:34.188278Z"},"papermill":{"duration":0.523706,"end_time":"2022-02-24T05:33:13.977058","exception":false,"start_time":"2022-02-24T05:33:13.453352","status":"completed"},"tags":[]},"outputs":[],"source":["X = featurization.fit_transform(train.drop('season', axis=1))\n","y = one_hot_final.fit_transform(np.array(train['season']).reshape(-1, 1))\n","\n","X_test = featurization.transform(test.drop('season', axis=1))"]},{"cell_type":"code","execution_count":38,"id":"51083b54","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:14.498677Z","iopub.status.busy":"2022-02-24T05:33:14.498021Z","iopub.status.idle":"2022-02-24T05:33:14.556473Z","shell.execute_reply":"2022-02-24T05:33:14.555922Z","shell.execute_reply.started":"2022-01-24T08:17:34.460557Z"},"papermill":{"duration":0.320436,"end_time":"2022-02-24T05:33:14.556623","exception":false,"start_time":"2022-02-24T05:33:14.236187","status":"completed"},"tags":[]},"outputs":[],"source":["X_train, X_val, y_train, y_val = train_test_split(X.toarray(), y.toarray(), \n","                                                  random_state=42, test_size=0.2)"]},{"cell_type":"code","execution_count":39,"id":"c4f7afd3","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:15.090291Z","iopub.status.busy":"2022-02-24T05:33:15.089529Z","iopub.status.idle":"2022-02-24T05:33:15.130145Z","shell.execute_reply":"2022-02-24T05:33:15.130632Z","shell.execute_reply.started":"2022-01-24T08:17:34.521829Z"},"papermill":{"duration":0.316415,"end_time":"2022-02-24T05:33:15.130828","exception":false,"start_time":"2022-02-24T05:33:14.814413","status":"completed"},"tags":[]},"outputs":[],"source":["model = keras.models.Sequential([\n","    keras.layers.Input(shape=(X.shape[1], )),\n","    keras.layers.Dense(128, activation='relu'),\n","    keras.layers.Dropout(0.3),\n","    keras.layers.Dense(64, activation='relu'),\n","    keras.layers.Dropout(0.2),\n","    keras.layers.Dense(16, activation='relu'),\n","    keras.layers.Dense(4, activation='softmax')\n","])"]},{"cell_type":"code","execution_count":40,"id":"1dc55b55","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:15.655896Z","iopub.status.busy":"2022-02-24T05:33:15.654606Z","iopub.status.idle":"2022-02-24T05:33:15.659306Z","shell.execute_reply":"2022-02-24T05:33:15.659839Z","shell.execute_reply.started":"2022-01-24T08:17:34.644532Z"},"papermill":{"duration":0.271348,"end_time":"2022-02-24T05:33:15.660013","exception":false,"start_time":"2022-02-24T05:33:15.388665","status":"completed"},"tags":[]},"outputs":[],"source":["model.compile('adam', loss='categorical_crossentropy', metrics=['accuracy'])"]},{"cell_type":"code","execution_count":41,"id":"83196521","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:16.197459Z","iopub.status.busy":"2022-02-24T05:33:16.196354Z","iopub.status.idle":"2022-02-24T05:33:16.207197Z","shell.execute_reply":"2022-02-24T05:33:16.20803Z","shell.execute_reply.started":"2022-01-24T08:17:35.535764Z"},"papermill":{"duration":0.287164,"end_time":"2022-02-24T05:33:16.208284","exception":false,"start_time":"2022-02-24T05:33:15.92112","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: \"sequential_2\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","dense_6 (Dense)              (None, 128)               9472      \n","_________________________________________________________________\n","dropout (Dropout)            (None, 128)               0         \n","_________________________________________________________________\n","dense_7 (Dense)              (None, 64)                8256      \n","_________________________________________________________________\n","dropout_1 (Dropout)          (None, 64)                0         \n","_________________________________________________________________\n","dense_8 (Dense)              (None, 16)                1040      \n","_________________________________________________________________\n","dense_9 (Dense)              (None, 4)                 68        \n","=================================================================\n","Total params: 18,836\n","Trainable params: 18,836\n","Non-trainable params: 0\n","_________________________________________________________________\n"]}],"source":["model.summary()"]},{"cell_type":"code","execution_count":42,"id":"e977d24b","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:16.731809Z","iopub.status.busy":"2022-02-24T05:33:16.731113Z","iopub.status.idle":"2022-02-24T05:33:56.979584Z","shell.execute_reply":"2022-02-24T05:33:56.980109Z","shell.execute_reply.started":"2022-01-24T08:17:35.553545Z"},"papermill":{"duration":40.511995,"end_time":"2022-02-24T05:33:56.980308","exception":false,"start_time":"2022-02-24T05:33:16.468313","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Epoch 1/25\n","535/535 [==============================] - 2s 3ms/step - loss: 1.0760 - accuracy: 0.4780 - val_loss: 0.9548 - val_accuracy: 0.4986\n","Epoch 2/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.9451 - accuracy: 0.5008 - val_loss: 0.8837 - val_accuracy: 0.5011\n","Epoch 3/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.8796 - accuracy: 0.5115 - val_loss: 0.8399 - val_accuracy: 0.5158\n","Epoch 4/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.8372 - accuracy: 0.5152 - val_loss: 0.7961 - val_accuracy: 0.5108\n","Epoch 5/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.8061 - accuracy: 0.5224 - val_loss: 0.7712 - val_accuracy: 0.5132\n","Epoch 6/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7846 - accuracy: 0.5199 - val_loss: 0.7596 - val_accuracy: 0.5088\n","Epoch 7/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7699 - accuracy: 0.5212 - val_loss: 0.7565 - val_accuracy: 0.5135\n","Epoch 8/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7634 - accuracy: 0.5194 - val_loss: 0.7457 - val_accuracy: 0.5154\n","Epoch 9/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7552 - accuracy: 0.5232 - val_loss: 0.7400 - val_accuracy: 0.5143\n","Epoch 10/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7510 - accuracy: 0.5225 - val_loss: 0.7370 - val_accuracy: 0.5178\n","Epoch 11/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7475 - accuracy: 0.5235 - val_loss: 0.7351 - val_accuracy: 0.5143\n","Epoch 12/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7456 - accuracy: 0.5243 - val_loss: 0.7336 - val_accuracy: 0.5157\n","Epoch 13/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7425 - accuracy: 0.5287 - val_loss: 0.7319 - val_accuracy: 0.5143\n","Epoch 14/25\n","535/535 [==============================] - 2s 4ms/step - loss: 0.7380 - accuracy: 0.5278 - val_loss: 0.7329 - val_accuracy: 0.5115\n","Epoch 15/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7391 - accuracy: 0.5249 - val_loss: 0.7284 - val_accuracy: 0.5129\n","Epoch 16/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7379 - accuracy: 0.5263 - val_loss: 0.7303 - val_accuracy: 0.5149\n","Epoch 17/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7355 - accuracy: 0.5260 - val_loss: 0.7333 - val_accuracy: 0.5160\n","Epoch 18/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7346 - accuracy: 0.5296 - val_loss: 0.7288 - val_accuracy: 0.5133\n","Epoch 19/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7324 - accuracy: 0.5290 - val_loss: 0.7301 - val_accuracy: 0.5101\n","Epoch 20/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7320 - accuracy: 0.5288 - val_loss: 0.7273 - val_accuracy: 0.5161\n","Epoch 21/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7318 - accuracy: 0.5323 - val_loss: 0.7273 - val_accuracy: 0.5130\n","Epoch 22/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7302 - accuracy: 0.5292 - val_loss: 0.7264 - val_accuracy: 0.5123\n","Epoch 23/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7297 - accuracy: 0.5266 - val_loss: 0.7253 - val_accuracy: 0.5142\n","Epoch 24/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7299 - accuracy: 0.5292 - val_loss: 0.7252 - val_accuracy: 0.5131\n","Epoch 25/25\n","535/535 [==============================] - 2s 3ms/step - loss: 0.7285 - accuracy: 0.5299 - val_loss: 0.7270 - val_accuracy: 0.5120\n"]}],"source":["history_ = model.fit(X_train, y_train, \n","                     validation_data=(X_val, y_val), \n","                     epochs=25, batch_size=64)"]},{"cell_type":"code","execution_count":43,"id":"d5c083b3","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:33:58.134898Z","iopub.status.busy":"2022-02-24T05:33:58.13418Z","iopub.status.idle":"2022-02-24T05:33:58.360304Z","shell.execute_reply":"2022-02-24T05:33:58.359656Z","shell.execute_reply.started":"2022-01-24T08:19:11.968052Z"},"papermill":{"duration":0.903959,"end_time":"2022-02-24T05:33:58.360467","exception":false,"start_time":"2022-02-24T05:33:57.456508","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["plt.plot(history_.history['loss'], '-r')\n","plt.plot(history_.history['val_loss'], '-b')\n","plt.legend()\n","plt.show()"]},{"cell_type":"markdown","id":"90c8f09d","metadata":{"papermill":{"duration":0.478556,"end_time":"2022-02-24T05:33:59.31545","exception":false,"start_time":"2022-02-24T05:33:58.836894","status":"completed"},"tags":[]},"source":["# Inference🛰"]},{"cell_type":"code","execution_count":44,"id":"58996234","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:34:00.339759Z","iopub.status.busy":"2022-02-24T05:34:00.33899Z","iopub.status.idle":"2022-02-24T05:34:01.040123Z","shell.execute_reply":"2022-02-24T05:34:01.039417Z","shell.execute_reply.started":"2022-01-24T08:19:12.197183Z"},"papermill":{"duration":1.185111,"end_time":"2022-02-24T05:34:01.040267","exception":false,"start_time":"2022-02-24T05:33:59.855156","status":"completed"},"tags":[]},"outputs":[],"source":["test_preds_final = model.predict(X_test.toarray())"]},{"cell_type":"code","execution_count":45,"id":"0cd7bfea","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:34:02.003844Z","iopub.status.busy":"2022-02-24T05:34:02.002331Z","iopub.status.idle":"2022-02-24T05:34:05.050168Z","shell.execute_reply":"2022-02-24T05:34:05.050675Z","shell.execute_reply.started":"2022-01-24T08:19:13.466035Z"},"papermill":{"duration":3.532503,"end_time":"2022-02-24T05:34:05.050928","exception":false,"start_time":"2022-02-24T05:34:01.518425","status":"completed"},"tags":[]},"outputs":[],"source":["for i in range(sample_sub.shape[0]):\n","    sample_sub.loc[i, 'season'] = one_hot_final.inverse_transform(\n","        np.array(test_preds_final[i]).reshape(1, -1))[0][0]"]},{"cell_type":"code","execution_count":46,"id":"4159b228","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:34:06.011809Z","iopub.status.busy":"2022-02-24T05:34:06.011138Z","iopub.status.idle":"2022-02-24T05:34:06.020791Z","shell.execute_reply":"2022-02-24T05:34:06.021385Z","shell.execute_reply.started":"2022-01-24T08:19:16.55899Z"},"papermill":{"duration":0.49412,"end_time":"2022-02-24T05:34:06.021544","exception":false,"start_time":"2022-02-24T05:34:05.527424","status":"completed"},"tags":[]},"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>season</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>18316</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>18317</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>18318</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>18319</th>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>18320</th>\n","      <td>u</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>18321 rows × 1 columns</p>\n","</div>"],"text/plain":["      season\n","0          u\n","1          u\n","2          u\n","3          u\n","4          u\n","...      ...\n","18316      u\n","18317      u\n","18318      u\n","18319      u\n","18320      u\n","\n","[18321 rows x 1 columns]"]},"execution_count":46,"metadata":{},"output_type":"execute_result"}],"source":["sample_sub"]},{"cell_type":"code","execution_count":47,"id":"0c150123","metadata":{"execution":{"iopub.execute_input":"2022-02-24T05:34:06.981015Z","iopub.status.busy":"2022-02-24T05:34:06.980311Z","iopub.status.idle":"2022-02-24T05:34:07.014276Z","shell.execute_reply":"2022-02-24T05:34:07.014879Z","shell.execute_reply.started":"2022-01-24T08:19:16.575656Z"},"papermill":{"duration":0.514208,"end_time":"2022-02-24T05:34:07.01507","exception":false,"start_time":"2022-02-24T05:34:06.500862","status":"completed"},"tags":[]},"outputs":[],"source":["sample_sub.to_csv('submission.csv', 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