To maximize the margin between classes
To minimize prediction errors
To classify data points based on features
To perform unsupervised learning
Answer is Wrong!
Answer is Right!
The correct answer is C. To classify data points based on features.
A naive Bayes classifier is a probabilistic machine learning model that uses Bayes’ theorem to classify data points. It is a simple and effective model that is often used for text classification, spam filtering, and other tasks where the data can be easily represented as a set of features.
The naive Bayes classifier assumes that the features are independent of each other, which is often not the case
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