Segment a numeric variable based on a dichotomous dependent variable by using the weight of evidence (WOE) approach (Ref: Siddiqi, N. (2006) <doi:10.1002/9781119201731.biblio>). The underlying algorithm adopts a recursive approach to create segments that are diverse in respect of their WOE values and meet the demands of user-defined parameters. The algorithm also aims to maintain a monotonic trend in WOE values of consecutive segments. As such, it can be particularly helpful in improving robustness of linear and logistic regression models.
| Version: | 0.2.1 |
| Depends: | R (≥ 3.4.0) |
| Imports: | dplyr |
| Suggests: | smbinning |
| Published: | 2019-01-23 |
| Author: | Kashish Soien |
| Maintainer: | Kashish Soien <kashish.soien19 at gmail.com> |
| BugReports: | https://github.com/kraken19/woeR/issues |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | woeR results |
| Reference manual: | woeR.pdf |
| Package source: | woeR_0.2.1.tar.gz |
| Windows binaries: | r-devel: woeR_0.2.1.zip, r-release: woeR_0.2.1.zip, r-oldrel: woeR_0.2.1.zip |
| macOS binaries: | r-release: woeR_0.2.1.tgz, r-oldrel: woeR_0.2.1.tgz |
| Old sources: | woeR archive |
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