Provides a set of functions that can be used to obtain better predictive performance on cost-sensitive and cost/benefits tasks (for both regression and classification). This includes re-sampling approaches that modify the original data set biasing it towards the user preferences.

Author | Paula Branco [aut, cre], Rita Ribeiro [aut, ctb], Luis Torgo [aut, ctb] |

Date of publication | 2016-07-13 16:17:09 |

Maintainer | Paula Branco <paobranco@gmail.com> |

License | GPL (>= 2) |

Version | 0.0.5 |

https://github.com/paobranco/UBL |

**CNNClassif:** Condensed Nearest Neighbors strategy for multiclass...

**ENNClassif:** Edited Nearest Neighbor for multiclass imbalanced problems

**gaussNoiseClassif:** Introduction of Gaussian Noise for the generation of...

**gaussNoiseRegress:** Introduction of Gaussian Noise for the generation of...

**ImbC:** Synthetic Imbalanced Data Set for a Multi-class Task

**ImbR:** Synthetic Regression Data Set

**ImpSampClassif:** Importance Sampling algorithm for imbalanced classification...

**ImpSampRegress:** Importance Sampling algorithm for imbalanced regression...

**NCLClassif:** Neighborhood Cleaning Rule (NCL) algorithm for multiclass...

**OSSClassif:** One-sided selection strategy for handling multiclass...

**phi:** Relevance function.

**phiControl:** Estimation of parameters used for obtaining the relevance...

**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

UBL

UBL/inst

UBL/inst/CITATION

UBL/tests

UBL/tests/testthat.R

UBL/tests/testthat

UBL/tests/testthat/testSmoteClassif.R

UBL/src

UBL/src/neighbours.f90

UBL/src/phi.f90

UBL/NAMESPACE

UBL/data

UBL/data/ImbR.rda

UBL/data/ImbC.rda

UBL/R

UBL/R/gaussNoiseRegress.R
UBL/R/ImpSampClassif.R
UBL/R/Neighbours.R
UBL/R/phiFunc.R
UBL/R/randUnderClassif.R
UBL/R/TomekClassif.R
UBL/R/gaussNoiseClassif.R
UBL/R/smoteClassif.R
UBL/R/ImpSampRegress.R
UBL/R/randOverClassif.R
UBL/R/CNNClassif.R
UBL/R/smoteRegress.R
UBL/R/NCLClassif.R
UBL/R/OSSClassif.R
UBL/R/zzz.R
UBL/R/ENNClassif.R
UBL/R/CallFPhi.R
UBL/R/randOverRegress.R
UBL/R/randUnderRegress.R
UBL/MD5

UBL/DESCRIPTION

UBL/man

UBL/man/OSSClassif.Rd
UBL/man/ImpSampRegress.Rd
UBL/man/smoteRegress.Rd
UBL/man/randUnderClassif.Rd
UBL/man/UBL-package.Rd
UBL/man/randUnderRegress.Rd
UBL/man/CNNClassif.Rd
UBL/man/ImbR.Rd
UBL/man/TomekClassif.Rd
UBL/man/smoteClassif.Rd
UBL/man/randOverClassif.Rd
UBL/man/gaussNoiseClassif.Rd
UBL/man/gaussNoiseRegress.Rd
UBL/man/ImbC.Rd
UBL/man/NCLClassif.Rd
UBL/man/ImpSampClassif.Rd
UBL/man/phi.Rd
UBL/man/randOverRegress.Rd
UBL/man/phiControl.Rd
UBL/man/ENNClassif.Rd
UBL/CHANGES

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