Package: ROSE 0.0-4

ROSE: Random Over-Sampling Examples

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.

Authors:Nicola Lunardon, Giovanna Menardi, Nicola Torelli

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# Install 'ROSE' in R:
install.packages('ROSE', repos = c('https://nicolalunardon.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

6.74 score 4 stars 2 packages 1.5k scripts 16k downloads 131 mentions 5 exports 0 dependencies

Last updated 3 years agofrom:b0d750fcd4. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-winOKNov 01 2024
R-4.5-linuxOKNov 01 2024
R-4.4-winNOTENov 01 2024
R-4.4-macNOTENov 01 2024
R-4.3-winNOTENov 01 2024
R-4.3-macNOTENov 01 2024

Exports:accuracy.measovun.sampleroc.curveROSEROSE.eval

Dependencies: