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

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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.0.6 by Paula Branco, 2 months ago

Report a bug at

Browse source code at

Authors: Paula Branco [aut, cre], Rita Ribeiro [aut, ctb], Luis Torgo [aut, ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Depends on methods, grDevices, graphics, stats, MBA, gstat, automap, sp, randomForest

Suggests MASS, rpart, testthat, DMwR, ggplot2, e1071

See at CRAN