The BernoulliNB is a classification algorithm provided by the scikit-learn library in Python. It is a variant of the Naive Bayes algorithm that specifically works with binary or boolean features. This algorithm is based on the assumption that all features are independent and follow a Bernoulli distribution. It calculates the probabilities of each class based on the occurrence of features and makes predictions by choosing the class with the highest probability. The BernoulliNB is commonly used for text classification tasks where the presence or absence of words in a document serves as features.
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