Racing for Unbalanced Methods Selection

A dataset is said to be unbalanced when the class of interest (minority class) is much rarer than normal behaviour (majority class). The cost of missing a minority class is typically much higher that missing a majority class. Most learning systems are not prepared to cope with unbalanced data and several techniques have been proposed. This package implements some of most well-known techniques and propose a racing algorithm to select adaptively the most appropriate strategy for a given unbalanced task.


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install.packages("unbalanced")

2.0 by Andrea Dal Pozzolo, 6 years ago


http://mlg.ulb.ac.be


Browse source code at https://github.com/cran/unbalanced


Authors: Andrea Dal Pozzolo , Olivier Caelen and Gianluca Bontempi


Documentation:   PDF Manual  


GPL (>= 3) license


Imports FNN, RANN

Depends on mlr, foreach, doParallel

Suggests randomForest, ROCR


Imported by alookr, hyperSMURF, themis.


See at CRAN