if the data is binary and we need to predict a z-test set, is a decision tree required or desirable? which variable is required for cross validation? when to use cross validation cross validation example if we use a binary variable with predictors, is cross validation necessary what is the purpose of cross validation cross validation of data sets if the value of z is a binary variable what does it do cross validation of a decision tree why is crossvalidation needed which data set is required for cross validation of decision trees? is cross validation necessary where is cross validation necessary when to use $k$ cross validation how to do $kfold cross validation on data which data sets are needed to construct tree data? what is the purpose of cross validation what is the reason to cross validate? what is the cross validation in data what is the purpose of cross validation of the decision tree?