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tf-idf vectorizer's use_idf parameter explanation

原文 2018-06-18 07:49:36 0 1 python/ machine-learning/ scikit-learn/ tfidfvectorizer

What is the use of use_idf parameter do in tfidf Vectorizer? Documentation doesn't give much explantion about it. can someone explain it?

1 answers

If use_idf is set to True (which is the default), then inverse document frequency is taken into account during transformation. What this causes is that tokens that appear in a lot of documents will be automatically deemed less informative than those that appear in fewer documents.

If you set it to False , only term-frequency (count of words in a document) is used.

Check this good explanation on Wikipedia .

TF-IDF vectorizer with python

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NotFittedError: The TF-IDF vectorizer is not fitted

TF-IDF Vectorizer Search Query Python

Implementing a TF-IDF Vectorizer from Scratch

faster sklearn tf-idf vectorizer

Converting count vectorizer to tf-idf

Building a TF-IDF Vectorizer from Scratch

Tokenize sentence based on existing punctuation (TF-IDF vectorizer)

Word Cloud built out of TF-IDF Vectorizer function

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tf-idf vectorizer's use_idf parameter explanation

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solution1 4 ACCPTED 2018-06-18 08:24:47

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4 ACCPTED 2018-06-18 08:24:47