Explain Naive Bayes Classification Algorithm with a suitable example.

Question

19 Mar 2025

Answer :

Word Count : 292

Naive Bayes is a probabilistic machine learning algorithm based on applying Bayes’ theorem with strong (naive) independence assumptions. It is commonly used for classification tasks and is particularly effective for problems involving large datasets with categorical input variables. The key idea is to predict the class of a given instance based on the features of the instance, treating ________ _____ __________ __________ ________ _________ ___ _______ ___ ___ ____.
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