A typical example of the Naïve Bayes classifier in Machine Learning involves classifying an email as spam or not spam based on word frequencies. First, calculate prior probabilities of each class and likelihood of features using training data. Then apply Bayes’ theorem to compute posterior probabilities for a new email. Finally, assign the class with the highest probability as the predicted output.
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