Which of the following statements are true with regard to Naive Bayes? (Select all that apply.) O Numerical predictor variables may be used without any transformation. O It makes several assumptions about the data, including that they are normally distributed. O There could be problems when a predictor category is not present in the training data. It requires a large number of observations.You have fit a Naive Bayes classification model where you focus on two predictors. Online (whether or not the customer is an active user of online banking services) and Credit Card (abbreviated CC below) (does the customer hold a credit card issued by the bank), and the outcome Personal Loan (abbreviated Loan below). Below is the tabular summary of the data. Compute and match the following conditional probabilities to the correct answer. Tabulate Tabulate Validation = Training Validation = Training Online CreditCard Personal Loan 0 1 Personal Loan 0 1090 1624 2714 0 1932 782 2714 107 179 286 200 86 286 2000 rows have been excluded. 2000 rows have been excluded. P (CC = 1|Loan = 1) (the proportion of credit card holders among the loan acceptors) [ Choose ] P (CC = 1|Loan = 0) [ Choose ] P (Online = 1 Loan = 0) [ Choose ] [ Choose 86/286 - 0.301 1624/2714 - 0.598 782/2714 = 0.288