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. The references including: 1 Refaat, M. (2011, ISBN: 9781447511199). Credit Risk Scorecard: Development and Implementation Using SAS; 2 Bezdek, James C.FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences (0098-3004),<doi:10.1016/0098-3004(84)90020-7>.
Version: 1.3.1 Depends: R (≥ 2.10) Imports: data.table, dplyr, ggplot2, foreach, doParallel, glmnet, rpart, cli, xgboost Suggests: pdp, pmml, XML, knitr, gbm, randomForest, rmarkdown Published: 2022-01-07 DOI: 10.32614/CRAN.package.creditmodel Author: Dongping Fan [aut, cre] Maintainer: Dongping Fan <fdp at pku.edu.cn> License: AGPL-3 NeedsCompilation: no Materials: README, NEWS In views: MissingData CRAN checks: creditmodel results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=creditmodel to link to this page.
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