The web site17 for the MLC++ software package contains a number of

machine learning data sets. The "churn" data set was developed to predict

telecom customer churn based on information about their account. The data

files state that the data are "artificial based on claims similar to real world."

The data consist of 19 predictors related to the customer account, such

as the number of customer service calls, the area code, and the number of

minutes. The outcome is whether the customer churned.

17 http://www.sgi.com/tech/mlc.

328 12 Discriminant Analysis and Other Linear Classification Models

The data are contained in the C50 package and can be loaded using:

> library(C50)

> data(churn)

> ## Two objects are loaded: churnTrain and churnTest

> str(churnTrain)

> table(churnTrain$Class)

(a) Explore the data by visualizing the relationship between the predictors

and the outcome. Are there important features of the predictor data

themselves, such as between-predictor correlations or degenerate distributions?

Can functions of more than one predictor be used to model the