Package: UBL 0.0.7

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.

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

UBL_0.0.7.tar.gz
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UBL.pdf |UBL.html✨
UBL/json (API)

Peer review:

Bug tracker:https://github.com/paobranco/ubl/issues

On CRAN:

32 exports 32 stars 2.93 score 55 dependencies 1 dependents 3 mentions 146 scripts 453 downloads

Last updated 3 years agofrom:d1a9ab4c68. Checks:OK: 4 WARNING: 5. Indexed: yes.

Exports:AdasynClassifBaggingRegressBagModelCNNClassifdistancesENNClassifEvalClassifMetricsEvalRegressMetricsGaussNoiseClassifGaussNoiseRegressNCLClassifneighboursOSSClassifphiphi.controlpredictRandOverClassifRandOverRegressRandUnderClassifRandUnderRegressReBaggRegressshowSMOGNClassifSMOGNRegressSmoteClassifSmoteRegressTomekClassifUtilInterpolUtilOptimClassifUtilOptimRegressWERCSClassifWERCSRegress

Dependencies:abindautomapBHclassclassIntclicolorspaceDBIe1071fansifarverFNNggplot2gluegstatgtableintervalsisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixMBAmgcvmunsellnlmepillarpkgconfigplyrproxyR6randomForestRColorBrewerRcppreshaperlangs2scalessfsftimespspacetimestarstibbleunitsutf8vctrsviridisLitewithrwkxtszoo