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AI & Machine Learning · Intermediate

Naive Bayes

A probabilistic classifier based on Bayes' theorem that assumes features are independent given the class.

Definition

Naive Bayes computes the probability of each class from feature likelihoods and priors. Despite its unrealistic independence assumption it is fast, needs little data and works well for text classification such as spam filtering.

Example

Classifying emails as spam using word frequencies.

Exam tip

Naive refers to the conditional independence assumption.

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