Machine Learning with R Cookbook - Second Edition

How it works...

In this recipe, we perform feature selection using the caret package. As there are factor-coded attributes within the dataset, we first use a function called model.matrix to transform the factor-coded attributes into multiple binary attributes. Therefore, we transform the international_plan attribute to intl_yes and intl_no. Additionally, we transform the voice_mail_plan attribute to voice_yes and voice_no.

Next, we set up control parameters for training using the cross-validation method, cv, with the linear discriminant function, ldaFuncs. Then, we use the recursive feature elimination, rfe, to perform feature selection with the use of the control function, ldaFuncs. The rfe function generates the summary of feature selection, ...