Answer / Ambreesh Kumar

Naive Bayes is a popular probabilistic machine learning algorithm used for classification tasks. It is based on Bayes' theorem with an assumption of independence between features (naively assuming that the presence of a particular feature does not affect the probability of occurrence of other features). The algorithm calculates the posterior probabilities of each class given the features by multiplying the prior probabilities and the likelihoods, which are the conditional probabilities of each feature given a specific class.

Despite its simplifying assumption, Naive Bayes has proven to be effective for text classification, spam filtering, and other tasks where data is high-dimensional and noisy.

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