The 'scorecard' package makes the development of credit risk scorecard easier and efficient by providing functions for some common tasks, such as data partition, variable selection, woe binning, scorecard scaling, performance evaluation and report generation. These functions can also used in the development of machine learning models. The references including: 1. Refaat, M. (2011, ISBN: 9781447511199). Credit Risk Scorecard: Development and Implementation Using SAS. 2. Siddiqi, N. (2006, ISBN: 9780471754510). Credit risk scorecards. Developing and Implementing Intelligent Credit Scoring.
Version: | 0.3.0 |
Depends: | R (≥ 3.5.0) |
Imports: | data.table (≥ 1.10.0), ggplot2, gridExtra, foreach, doParallel, parallel, openxlsx, stringi |
Suggests: | knitr, rmarkdown, pkgdown, testthat |
Published: | 2020-04-10 |
Author: | Shichen Xie [aut, cre] |
Maintainer: | Shichen Xie <xie at shichen.name> |
BugReports: | https://github.com/ShichenXie/scorecard/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/ShichenXie/scorecard |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | scorecard results |
Reference manual: | scorecard.pdf |
Vignettes: |
Developing a Credit Scorcard |
Package source: | scorecard_0.3.0.tar.gz |
Windows binaries: | r-devel: scorecard_0.3.0.zip, r-release: scorecard_0.3.0.zip, r-oldrel: scorecard_0.3.0.zip |
macOS binaries: | r-release: scorecard_0.3.0.tgz, r-oldrel: scorecard_0.3.0.tgz |
Old sources: | scorecard archive |
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