What is Naive Bayes classifier and why is it called 'naive'?

Naive Bayes is a probabilistic classifier based on Bayes’ theorem assuming feature independence.

Naive Bayes applies Bayes' theorem: P(Y|X) = P(X|Y)P(Y)/P(X). It assumes all features are conditionally independent given the class label, which is rarely true in reality—hence 'naive'. Despite this, it performs well in text classification due to high-dimensional sparse data.