ABSTRACT
This chapter discusses and implements the Naive Rule – a rudimentary model that can be used as a benchmark to compare other more sophisticated algorithms. The Naive Bayes make a simplifying assumption on the Complete Bayes which will both improve its ability to classify and the speed of the classification process. The chapter covers various concepts in probability, including events and conditional probability and discusses Complete Bayes classifier and observational units and records. It uses a simple debugging technique in R to see the contents of args within the program. The chapter helps the readers to try the same debugging technique using HouseVotes84. It also discusses how to clean up a general dataframe within the body of CompleteBayes_singleClassEllipsis ().
