<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Evaluation Metrics for Customer Scoring Models Depending on
Binary Classifiers</dc:title>
  <dc:title>R package CustomerScoringMetrics version 1.0.0</dc:title>
  <dc: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 &amp; Linoff (2004, ISBN:0-471-47064-3), Witten and Frank (2005, 0-12-088407-0) and Blattberg, Kim &amp; 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.</dc:description>
  <dc:type>Software</dc:type>
  <dc:creator>Koen W. De Bock &lt;kdebock@audencia.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Koen W. De Bock</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2018-04-06</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=CustomerScoringMetrics</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.CustomerScoringMetrics</dc:identifier>
</oai_dc:dc>