I need support with this Engineering question so I can learn better.
1. Consider the following Training Data Set: • Apply the Naïve Bayesian Classifier to this data set and compute the probability score for P(y = 1X) for X = (1,0,0) Show your work Your Thoughts?Training Data Set
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 loglikelihoods 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?

