Differentiate term frequency from inverse document frequency matrix.

783    Asked by FukudaAshikaga in Data Science , Asked on Nov 17, 2019
Answered by Fukuda Ashikaga

In term frequency matrix, it finds out the relevance of words present in a document. It assumes the more frequently the word appears in a document, the more relevant is the word in the context. It works on the formula given below

TF = 1 + log (TF) if TF > 0

Where TF is the term frequency.

On the other hand, inverse document matrix assumes that words appear less in a document are more informative. It works on the formula given below

IDF = log (N/DF)

where N -the number of documents and

DF -the number of documents in which the word occurs.



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