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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 359.2 kB | noarch/r-scorecard-0.4.1-r41h785f33e_0.conda  1 year and 11 months ago 1151 main
conda 358.6 kB | noarch/r-scorecard-0.4.1-r42h785f33e_0.conda  1 year and 11 months ago 1148 main

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