Main function of the package.
It produces Classification Trees with Branch-Exclusive variables.
Uses a Validation Set to select the best trees within the list of pruned trees.
Produces a variable important analysis using the mean decrease in node impurity
Generates a random forest of BEST trees
Classify a set of new observation points
Performs Bootstrap Aggregating of BEST trees
Data generated according to decision tree for simulation purposes
Data generated according to decision tree for simulation purposes
Classify a new observation point
Emits prediction from a forest of BEST's
Computes the proportion of matching terms in two vectors of the same length.
Used to compute the accuracy for prediction on test set.
Quickly build the Available Variable list necessary for BEST
This list contains details as to which variables is available for the partitioning.
It also contains which variables are gating variables.