Chapter 5
Classification – Tree, Lazy, and Probabilistic
Section 11
Classifying data with the Naïve Bayes Classifier
The Naïve Bayes classifier is based on applying Bayes’ theorem with a strong independent assumption. - Specify the variables as first input parameters and churn label as the second input parameter in the function call - Assign the classification model to the classifier variable - Use a confusion matrix to calculate the performance measurement