Explain Naïve Bayes Classification Algorithm with a suitable example.
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 shown to perform well, especially for large datasets and _______ ____ _________ ___ __________ ____ _______ _____ ________ ______.
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