Answer Posted / Hem Chandra Pant

Naive Bayes is called 'naive' because it makes an assumption that the features (or attributes) of a problem are conditionally independent given the class variable. This simplifying assumption allows for efficient computation, but may not hold true in real-world scenarios. However, despite this 'naiveness', Naive Bayes performs well in many practical applications due to its ability to capture complex probabilistic relationships among features.

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