Overview
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