Generate the monotonic binning and perform the woe (weight of evidence) transformation for the logistic regression used in the consumer credit scorecard development. The woe transformation is a piecewise transformation that is linear to the log odds. For a numeric variable, all of its monotonic functional transformations will converge to the same woe transformation.
| Version: | 0.4.2 |
| Depends: | R (≥ 3.3.3) |
| Imports: | stats, gbm, Rborist |
| Published: | 2021-07-31 |
| Author: | WenSui Liu |
| Maintainer: | WenSui Liu <liuwensui at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/statcompute/mob |
| NeedsCompilation: | no |
| CRAN checks: | mob results |
| Reference manual: | mob.pdf |
| Package source: | mob_0.4.2.tar.gz |
| Windows binaries: | r-devel: mob_0.4.2.zip, r-release: mob_0.4.2.zip, r-oldrel: mob_0.4.2.zip |
| macOS binaries: | r-release (arm64): mob_0.4.2.tgz, r-oldrel (arm64): mob_0.4.2.tgz, r-release (x86_64): mob_0.4.2.tgz, r-oldrel (x86_64): mob_0.4.2.tgz |
| Old sources: | mob archive |
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