ROSE: a Package for Binary Imbalanced Learning
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| Authors | Nicola Lunardon, Giovanna Menardi, Nicola Torelli |
| Journal/Conference Name | {R |
| Paper Category | Other |
| Paper Abstract | The ROSE package provides functions to deal with binary classification problems in the presence of imbalanced classes. Artificial balanced samples are generated according to a smoothed bootstrap approach and allow for aiding both the phases of estimation and accuracy evaluation of a binary classifier in the presence of a rare class. Functions that implement more traditional remedies for the class imbalance and different metrics to evaluate accuracy are also provided. These are estimated by holdout, bootstrap, or cross-validation methods. |
| Date of publication | 2014 |
| Code Programming Language | R |
| Comment |
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