I extracted the text data from resumes and then applied TF-IDF (Term Frequency and Inverse Document Frequency) which tells how rare the word present in resumes based on that tf-idf score will come so that we predict that word as rare word and then we use it for classifying resumes.
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I extracted the text data from resumes and then applied TF-IDF (Term Frequency and Inverse Document Frequency) which tells how rare the word present in resumes based on that tf-idf score will come so that we predict that word as rare word and then we use it for classifying resumes.
Roopesh-Nallakshyam/NLTK-TF-IDF-Algorithm
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I extracted the text data from resumes and then applied TF-IDF (Term Frequency and Inverse Document Frequency) which tells how rare the word present in resumes based on that tf-idf score will come so that we predict that word as rare word and then we use it for classifying resumes.
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