Explain Naïve Bayes Classification Algorithm with a suitable exam

Question

Explain Naïve Bayes Classification Algorithm with a suitable example.

23 Jan 2025

Answer :

Word Count : 270

Naïve Bayes is a probabilistic classification algorithm based on Bayes' Theorem, which applies the principle of conditional probability. It assumes that the features used for classification are independent of each other, hence the term "naïve." Despite this assumption being often unrealistic, Naïve Bayes has been __________ _____ ____ ___ ________ ______ _____ ____.
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