Question

Which of the following statement is true about Bayes classifier? A. It always provides zero error when class distributions are known B. It always provides the lowest possible error when class distributions are known C. It may not always provide the lowest possible error when class distributions are known D. It always provides the lowest possible error when class distributions are estimated

Answer 1

I can't understand the question sorry

Answer 2

It always provides the lowest possible error when class distributions are estimated

Explanation:

Naive Bayes is a type of classifier which makes use of the Bayes Theorem.

It predicts club chances for every magnificence which include the opportunity that given document or statistics factor belongs to a specific magnificence.

The magnificence with the very best opportunity is taken into consideration because of the maximum possibly magnificence.

Naïve Bayes Classifier is one of the easy and simplest Classification algorithms which facilitates in constructing the quick gadget getting to know fashions that may make short predictions.

It is a probabilistic classifier, because of this that it predicts on the premise of the opportunity of an object.