The Naïve Bayes classifier is also a probability-based classifier, which is based on applying the Bayes theorem with a strong independent assumption. In this recipe, we will introduce how to classify data with the Naïve Bayes classifier.
You need to have the first recipe completed by generating training and testing datasets.
Perform the following steps to classify the churn data with the Naïve Bayes classifier:
e1071library and employ the
naiveBayesfunction to build the classifier:
> library(e1071) > classifier=naiveBayes(trainset[, !names(trainset) %in% c("churn")], trainset$churn)
classifierto examine the function call, a-priori probability, and conditional ...