UBL: 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.

AuthorPaula Branco [aut, cre], Rita Ribeiro [aut, ctb], Luis Torgo [aut, ctb]
Date of publication2016-07-13 16:17:09
MaintainerPaula Branco <paobranco@gmail.com>
LicenseGPL (>= 2)
Version0.0.5
https://github.com/paobranco/UBL

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