#87 Machine Learning & Data Science Challenge 87
Bhagirath Deshani 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.
- 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
- 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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Written by
Bhagirath Deshani
Bhagirath Deshani
Hello everyone! I am Machine Learning Engineer. I am from India. I have been interested in machine learning since my engineering days. I have completed Andrew NG’s original Machine Learning course from Stanford University at Coursera and also completed the IBM course on Machine Learning and Deep Learning. Currently, I am working on Machine Learning and Data Science project. My goal is to use the skills I have acquired to solve real-world problems and make a positive impact on the world.