In a practical scenario, for which of the following cases Naive
Bayes Algorithm performs well?
A Discrete variables
B. Continuous variables
Answers
Answered by
0
Answer: A
Explanation:
Answered by
0
'Naive Bayes Algorithm' performs well Discrete variables.
Option (A)
Explanation:
- 'Naive Bayes' uses a similar approach to foresee the probability of several classes based on different attributes.
- The 'Naive Bayes' algorithm enables speedy, very scalable type building and scoring. It scales linearly to the number of 'predictors' and rows. Naive Bayes is used for both 'binary' and 'multi-class' classification problems.
- 'Naive Bayes' is commonly used when you have discrete features or your continue features follow a known distribution (even though non-parametric approaches can also be used).
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