creditmodel: Toolkit for Credit Modeling

Provides a highly efficient R tool suite for Credit Modeling, Analysis and Visualization. Contains infrastructure functionalities such as data exploration and preparation, missing values treatment, outliers treatment, variable derivation, variable selection, dimensionality reduction, grid search for hyper parameters, data mining and visualization, model evaluation, strategy analysis etc. This package is designed to make the development of binary classification models (machine learning based models as well as credit scorecard) simpler and faster. 1.Anderson, R. (2007). The credit scoring toolkit: Theory and practice for retail credit risk management and decision automation. 2.Find, S. (2012, ISBN13: 9780230347762). Credit scoring, response modelling and insurance rating:A practical guide to forecasting consumer behaviour.

Version: 1.1.3
Depends: R (≥ 3.3.0)
Imports: data.table, dplyr, ggplot2, gridExtra, glmnet, rpart, xgboost, gbm, randomForest, foreach, doParallel, pdp, pmml, XML, cli
Suggests: knitr, testthat
Published: 2019-09-13
Author: Dongping Fan [aut, cre]
Maintainer: Dongping Fan <fdp at pku.edu.cn>
License: AGPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: creditmodel results

Downloads:

Reference manual: creditmodel.pdf
Vignettes: Automated Model Development Process
Package source: creditmodel_1.1.3.tar.gz
Windows binaries: r-devel: creditmodel_1.1.3.zip, r-release: creditmodel_1.1.3.zip, r-oldrel: creditmodel_1.1.3.zip
OS X binaries: r-release: creditmodel_1.1.3.tgz, r-oldrel: creditmodel_1.1.3.tgz
Old sources: creditmodel archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=creditmodel to link to this page.