gsiddhad / Text-Classification

Text Classification using ML and DL

Text Classification

Text Classification using ML and DL

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Tc-nltk-tfidf - (Text Classification on NLTK Dataset using TFIDF)

• Tc-nltk-tfidf-rf (Random Forest)
• Tc-nltk-tfidf-dt (Decision Tree)
• Tc-nltk-tfidf-knn (K-Nearest Neighbours)

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Tc-nltk-r-tfidf - (Text Classification on NLTK Dataset using TFIDF with only Max Frequency)

• Tc-nltk-r-tfidf-rf (Random Forest)
• Tc-nltk-r-tfidf-dt (Decision Tree)
• Tc-nltk-r-tfidf-knn (K-Nearest Neighbours)

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Tc-nltk-lsa - (Text Classification on NLTK Dataset using TruncatedSVD)

• Tc-nltk-lsa-rf (Random Forest)
• Tc-nltk-lsa-dt (Decision Tree)
• Tc-nltk-lsa-knn (K-Nearest Neighbours)

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Tc-nltk-lstm - (Text Classification on NLTK Dataset using LSTM)

• Tc-nltk-lstm (Long Short Term Memory)
• Tc-nltk-lstm-rnn (Recurrent Neural Network with LSTM)

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Tc-nltk-lstm-topcat - (Text Classification on NLTK Dataset using Autoencoder)

• Tc-nltk-lstm-rnn-topcat (RNN with LSTM on top 5/10/20 Categories)

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Tc-reuters - (Text Classification on Original Reuters-21578 Dataset)

• Tc-reuters (NLTK vs Reuters-21578)