1. Consider the following Training Data Set:

• Apply the Naïve Bayesian Classifier to this data set and compute the probability score for P(y = 1|X) for X = (1,0,0)

Show your work

Your Thoughts?Training Data Set

X1

X2

X3

Y

1

1

1

0

1

1

0

0

0

0

0

0

0

1

0

1

1

0

1

1

0

1

1

1

2. List some prominent use cases of the Naïve Bayesian Classifier.

3. What gives the Naïve Bayesian Classifier the advantage of being computationally inexpensive?

4. Why should we use log-likelihoods rather than pure probability values in the Naïve Bayesian Classifier?

5. What is a confusion matrix and how it is used to evaluate the

effectiveness of the model?

6. Consider the following data set with two input features temperature and season

Your Thoughts?

  • What is the Naïve Bayesian assumption?
  • Is the Naïve Bayesian assumption satisfied for this problem?

Temperature

Season

Electricty Usage

-10 to 50 F

Winter

High

50 to 70 F

Winter

Low

70 to 85 F

Summer

Low

85 to 110 F

Summer

High

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