Classification Algorithms – Naive Bayes Review

Classification Algorithms – Naive Bayes Review

5 questions

1
point
1. 

What is the main Naive Bayes assumption?

Knowledge about the value of the class attribute indicates value of another attribute

Knowledge about the value of a particular attribute doesn’t tell us anything about the value of another attribute

Knowledge about the value of a particular attribute tells us everything we need to know about the class value

1
point
2. 

Even when the attribute independence assumption is violated, Naive Bayes scheme still works well.

False

True

1
point
3. 

In Naive Bayes – a prior probability is

Probability of event after evidence has been seen

Probability of an event before evidence has been seen

1
point
4. 

Naïve Bayes assumption allows for the evidence to be split into independent parts

False

True

1
point
5. 

Naive Bayes method would have a hard time learning from dataset that has

Many nominal attributes

Many numeric attributes

Many redundant attributes

Many irrelevant features

5 questions unanswered

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