An Implementation of Re-Sampling Approaches to Utility-Based Learning for Both Classification and Regression Tasks

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Documentation for package ‘UBL’ version 0.0.6

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UBL-package UBL: Utility-Based Learning
AdasynClassif ADASYN algorithm for unbalanced classification problems, both binary and multi-class.
CNNClassif Condensed Nearest Neighbors strategy for multiclass imbalanced problems
distances Distance matrix between all data set examples according to a selected distance metric.
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
neighbours Computation of nearest neighbours using a selected distance function.
OSSClassif One-sided selection strategy for handling multiclass imbalanced problems.
phi Relevance function.
phi.control Estimation of parameters used for obtaining the relevance function.
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
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.