utiml: Utilities for Multi-Label Learning (original) (raw)
Multi-label learning strategies and others procedures to support multi- label classification in R. The package provides a set of multi-label procedures such as sampling methods, transformation strategies, threshold functions, pre-processing techniques and evaluation metrics. A complete overview of the matter can be seen in Zhang, M. and Zhou, Z. (2014) <doi:10.1109/TKDE.2013.39> and Gibaja, E. and Ventura, S. (2015) A Tutorial on Multi-label Learning.
| Version: | 0.1.7 |
|---|---|
| Depends: | R (≥ 3.0.0), mldr (≥ 0.4.0), parallel, ROCR |
| Imports: | stats, utils, methods |
| Suggests: | C50, e1071, infotheo, kknn, knitr, randomForest, rmarkdown, markdown, rpart, testthat, xgboost (≥ 0.6-4) |
| Published: | 2021-05-31 |
| DOI: | 10.32614/CRAN.package.utiml |
| Author: | Adriano Rivolli [aut, cre] |
| Maintainer: | Adriano Rivolli |
| BugReports: | https://github.com/rivolli/utiml |
| License: | GPL-3 |
| URL: | https://github.com/rivolli/utiml |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | utiml results |
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