Question

15. Which of the following is true about Naive Bayes ?
a. Assumes that all the features in a dataset are equally important
b. Assumes that all the features in a dataset are independent
c. Both A and B
d. None of the above​

Answer 1

Answer:

both a and b s

Explanation:

both are correct

Answer 2

Out of the following options, option c) Both A and B is true for Naive Bayes.

• Naive Bayes is a classification technique based on Bayes’ Theorem with an assumption of independence among predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature.
• For example, a fruit may be considered to be an apple if it is red , round, and about 4 inches in diameter. Even if these features depend on each other or upon the existence of the other features, all of these properties independently contribute to the probability that this fruit is an apple and that is why it is known as ‘Naive’.
• Hence it is assumed that all features in a dataset are equally important and all the features in a dataset are independent.