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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "CustomerScoringMetrics" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'CustomerScoringMetrics: Evaluation Metrics for Customer Scoring Models Depending
  on Binary Classifiers'
version: 1.0.0
doi: 10.32614/CRAN.package.CustomerScoringMetrics
abstract: '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.'
authors:
- family-names: De Bock
  given-names: Koen W.
  email: kdebock@audencia.com
- email: kdebock@audencia.com
repository: https://koendebock.r-universe.dev
commit: 09f407d8ba99ad86e146dba7af98d4ad0c2d9189
date-released: '2018-04-06'
contact:
- family-names: De Bock
  given-names: Koen W.
  email: kdebock@audencia.com
- email: kdebock@audencia.com