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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.

copied from cf-staging / r-scorecard
Type Size Name Uploaded Downloads Labels
conda 365.8 kB | noarch/r-scorecard-0.4.4-r43h785f33e_1.conda  7 months and 27 days ago 660 main
conda 367.3 kB | noarch/r-scorecard-0.4.4-r44h785f33e_1.conda  7 months and 27 days ago 666 main
conda 366.3 kB | noarch/r-scorecard-0.4.4-r42h785f33e_0.conda  11 months and 17 days ago 878 main
conda 365.8 kB | noarch/r-scorecard-0.4.4-r43h785f33e_0.conda  11 months and 17 days ago 867 main

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