bstrap                  Performs bootstrap sampling of the (training)
                        dataset
construct.treeRK        Constructs a classification tree on the
                        (training) dataset, by implementing the RK
                        (Random 'K') algorithm
criteria.after.split.calculator
                        Calculates Entropy or Gini Index of a node
                        after a given split
criteria.calculator     Calculates Entropy or Gini Index of a
                        particular node before (or without) a split
cutoff.node.and.covariate.index.finder
                        Identifies optimal cutoff point of an impure
                        node for splitting after applying the 'rk'
                        (Random K) algorithm.
draw.treeRK             Creates a 'igraph' plot of a 'rktree'
ends.index.finder       Identifies numerical indices of the end nodes
                        of a 'rktree' from the matrix of hierarchical
                        flags.
forestRK                Builds up a random forest RK model based on the
                        given (training) dataset
get.tree.forestRK       Extracts the structure of one or more trees in
                        a forestRK object
importance.forestRK     Calculates Gini Importance or Mean Decrease
                        Impurity (same algorithm is used in
                        'scikit-learn') of each covariate that we
                        consider in the 'forestRK' model
importance.plot.forestRK
                        Generates importance 'ggplot' of the covariates
                        considered in the 'forestRK' model
mds.plot.forestRK       Makes 2D MDS (multidimensional scaling)
                        'ggplot' of the test observations based on the
                        predictions from a 'forestRK' model.
pred.forestRK           Make predictions on the test data based on the
                        forestRK model constructed from the training
                        data
pred.treeRK             Make predictions on the test observations based
                        on a rktree model
var.used.forestRK       Extract the list of covariates used to perform
                        the splits to generate a particular tree(s) in
                        a 'forestRK' object
x.organizer             Numericizing a data frame of covariates from
                        the original dataset via Binary or Numeric
                        Encoding
y.organizer             Numericize the vector containing categorical
                        class type('y') of the original data
