AdasynClassif           ADASYN algorithm for unbalanced classification
                        problems, both binary and multi-class.
CNNClassif              Condensed Nearest Neighbors strategy for
                        multiclass imbalanced problems
ENNClassif              Edited Nearest Neighbor for multiclass
                        imbalanced problems
EvalClassifMetrics      Utility metrics for assessing the performance
                        of utility-based classification tasks.
EvalRegressMetrics      Utility metrics for assessing the performance
                        of utility-based regression tasks.
GaussNoiseClassif       Introduction of Gaussian Noise for the
                        generation of synthetic examples to handle
                        imbalanced multiclass problems.
GaussNoiseRegress       Introduction of Gaussian Noise for the
                        generation of synthetic examples to handle
                        imbalanced regression problems
ImbC                    Synthetic Imbalanced Data Set for a Multi-class
                        Task
ImbR                    Synthetic Regression Data Set
ImpSampClassif          Importance Sampling algorithm for imbalanced
                        classification problems
ImpSampRegress          Importance Sampling algorithm for imbalanced
                        regression problems
NCLClassif              Neighborhood Cleaning Rule (NCL) algorithm for
                        multiclass imbalanced problems
OSSClassif              One-sided selection strategy for handling
                        multiclass imbalanced problems.
RandOverClassif         Random over-sampling for imbalanced
                        classification problems
RandOverRegress         Random over-sampling for imbalanced regression
                        problems
RandUnderClassif        Random under-sampling for imbalanced
                        classification problems
RandUnderRegress        Random under-sampling for imbalanced regression
                        problems
SmoteClassif            SMOTE algorithm for unbalanced classification
                        problems
SmoteRegress            SMOTE algorithm for imbalanced regression
                        problems
TomekClassif            Tomek links for imbalanced classification
                        problems
UBL-package             UBL: Utility-Based Learning
UtilInterpol            Utility surface obtained through methods for
                        spatial interpolation of points.
UtilOptimClassif        Optimization of predictions utility, cost or
                        benefit for classification problems.
UtilOptimRegress        Optimization of predictions utility, cost or
                        benefit for regression problems.
distances               Distance matrix between all data set examples
                        according to a selected distance metric.
neighbours              Computation of nearest neighbours using a
                        selected distance function.
phi                     Relevance function.
phi.control             Estimation of parameters used for obtaining the
                        relevance function.
