Manually solve the questions below by using the Nave Bayes Classifier: We conducted a survey to collect people's daily diets and try to build a

Manually solve the questions below by using the Naïve Bayes Classifier:

We conducted a survey to collect people's daily diets and try to build a model to predict whether their diets result in healthy conditions or not. The final results could be Yes, or No. Note: using green rows as training, and orange rows as testing.

Breakfast	Lunch	Dinner	Healthy?
Ham	Carnivorous	Beef	Y
Milk	Carnivorous	Beef	N
Bread	Veggie	Pork	N
Bread	Veggie	Veggie	Y
Ham	Veggie	Veggie	Y
Milk	Carnivorous	Pork	N
Bread	Carnivorous	Beef	N
Ham	Veggie	Pork	Y
Milk	Veggie	Pork	Y
Milk	Carnivorous	Veggie	N
Noddle	Carnivorous	Pork	?

1). [5 points] What is Laplace smoothing? And why do we need it in the Naïve Bayesian classifier?

2). [15 points] Using the Categorical Naive Bayesian Classification to make predictions on the test sets, present confusion matrix, and calculate accuracy, precision, recall, F1 measure, and specificity, by considering Y as a positive label

3). [20 points] Using the Categorical Naive Bayesian Classification to make predictions on the unseen data (note: building the model by using both the green and orange rows, and predicting the label for unseen data/last row)