Package: CustomerScoringMetrics
Type: Package
Title: Evaluation Metrics for Customer Scoring Models Depending on
        Binary Classifiers
Version: 1.0.0
Author: Koen W. De Bock
Maintainer: Koen W. De Bock <kdebock@audencia.com>
Description: Functions for evaluating and visualizing predictive model performance (specifically: binary classifiers) in the field of customer scoring. These metrics include lift, lift index, gain percentage, top-decile lift, F1-score, expected misclassification cost and absolute misclassification cost. See Berry & Linoff (2004, ISBN:0-471-47064-3), Witten and Frank (2005, 0-12-088407-0) and Blattberg, Kim & Neslin (2008, ISBN:978–0–387–72578–9) for details. Visualization functions are included for lift charts and gain percentage charts. All metrics that require class predictions offer the possibility to dynamically determine cutoff values for transforming real-valued probability predictions into class predictions.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-04-04 18:46:18 UTC; kdebock
Repository: CRAN
Date/Publication: 2018-04-06 10:39:01 UTC
Built: R 4.3.3; ; 2025-01-24 06:18:48 UTC; unix
