#87 Machine Learning & Data Science Challenge 87

#87 Machine Learning & Data Science Challenge 87

What do you understand by TF-IDF?

TF-IDF:

It stands for the term frequency-inverse document frequency.

TF-IDF weight:

  • It is a statistical measure used to evaluate how important a word is to a document in a collection or corpus.

  • The importance increases proportionally to the number of times a word appears in the document but is offset by the frequency of the word in the corpus.

  1. Term Frequency (TF):
  • It is a scoring of the frequency of the word in the current document.

  • Since every document is different in length, it is possible that a term would appear much more times in long documents than in shorter ones. The term frequency is often divided by the document length to normalize

  1. Inverse Document Frequency (IDF):
  • It is a scoring of how rare the word is across the documents. It is a measure of how rare a term is, the Rarer the term, and more is the IDF score.

Thus,