#87 Machine Learning & Data Science Challenge 87

Bhagirath Deshani Bhagirath Deshani
1 min read

Table of contents

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,

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Bhagirath Deshani
Bhagirath Deshani

Greetings. I am a machine learning engineer based in India, possessing a sustained interest in machine learning since my undergraduate studies. I have completed Stanford University's machine learning course (Andrew Ng) via Coursera, and IBM's machine learning and deep learning curriculum. My current focus is on machine learning and data science projects, aiming to leverage my expertise for impactful, real-world problem-solving.