Explain Naive Bayes Classifier and the principle on which it works?

Data Science, AI and ML
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Naive Bayes Classifier algorithm is a probabilistic model. This model works on the Bayes Theorem principle. The accuracy of Naive Bayes can be increased significantly by combining it with other kernel functions for making a perfect Classifier.

Bayes Theorem – This is a theorem which explains the conditional probability. If we need to identify the probability of occurrence of Event A provided the Event B has already occurred such cases are known as Conditional Probability.