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ROSE (version 0.0-3)

ROSE: Random Over-Sampling Examples

Description

The package provides functions to deal with binary classification problems in the presence of imbalanced classes. Synthetic balanced samples are generated according to ROSE (Menardi and Torelli, 2013). Functions that implement more traditional remedies to the class imbalance are also provided, as well as different metrics to evaluate a learner accuracy. These are estimated by holdout, bootstrap or cross-validation methods.

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Version

Install

install.packages('ROSE')

Monthly Downloads

11,956

Version

0.0-3

License

GPL-2

Maintainer

Nicola Lunardon

Last Published

July 15th, 2014

Functions in ROSE (0.0-3)

ROSE.eval

Evaluation of learner accuracy by ROSE
hacide

Half circle filled data
accuracy.meas

Metrics to evaluate a classifier accuracy in imbalanced learning
ROSE-package

ROSE: Random Over-Sampling Examples
ROSE

Generation of synthetic data by Randomly Over Sampling Examples (ROSE)
ovun.sample

Over-sampling, under-sampling, combination of over- and under-sampling.
roc.curve

ROC curve