Learn R Programming

ROSE (version 0.0-4)

Random Over-Sampling Examples

Description

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.

Copy Link

Version

Install

install.packages('ROSE')

Version

0.0-4

License

GPL-2

Maintainer

Last Published

June 14th, 2021

Functions in ROSE (0.0-4)

hacide

Half circle filled data
ovun.sample

Over-sampling, under-sampling, combination of over- and under-sampling.
accuracy.meas

Metrics to evaluate a classifier accuracy in imbalanced learning
roc.curve

ROC curve
ROSE.eval

Evaluation of learner accuracy by ROSE
ROSE

Generation of synthetic data by Randomly Over Sampling Examples (ROSE)
ROSE-package

ROSE: Random Over-Sampling Examples