Lec-8: Naive Bayes Classification Full Explanation with examples | Supervised Learning

00:00 – Naive Bayes classification
01:29 – Bayes’ Theorem
04:05 – Formula
07:36 – example

Naive Bayes is a family of probabilistic algorithms based on Bayes' Theorem, particularly suited for classification tasks. The "naive" assumption in Naive Bayes is that all features are independent given the class label, which simplifies the computation but might not hold true in real-world data.

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