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

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0.0.7 by Paula Branco, 7 months ago

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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, DMwR2, ggplot2, e1071

See at CRAN