Keyword-extraction

Dependencies:

1. PyPDF2
2. sklearn
3. pandas

Algorithm used

1. LDA : here

Linear Discriminant Analysis A classifier with a linear decision boundary, generated by fitting class conditional densities to the data and using Bayes’ rule. The model fits a Gaussian density to each class, assuming that all classes share the same covariance matrix. The fitted model can also be used to reduce the dimensionality of the input by projecting it to the most discriminative directions.

2. NMF : here Non-Negative Matrix Factorization (NMF)

Find two non-negative matrices (W, H) whose product approximates the non- negative matrix X. This factorization can be used for example for dimensionality reduction, source separation or topic extraction.

Final Image of keywords:

1. LDA :
2. NMF :