Package: CustomerScoringMetrics 1.0.0
CustomerScoringMetrics: Evaluation Metrics for Customer Scoring Models Depending on Binary Classifiers
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:
CustomerScoringMetrics_1.0.0.tar.gz
CustomerScoringMetrics_1.0.0.zip(r-4.5)CustomerScoringMetrics_1.0.0.zip(r-4.4)CustomerScoringMetrics_1.0.0.zip(r-4.3)
CustomerScoringMetrics_1.0.0.tgz(r-4.4-any)CustomerScoringMetrics_1.0.0.tgz(r-4.3-any)
CustomerScoringMetrics_1.0.0.tar.gz(r-4.5-noble)CustomerScoringMetrics_1.0.0.tar.gz(r-4.4-noble)
CustomerScoringMetrics_1.0.0.tgz(r-4.4-emscripten)CustomerScoringMetrics_1.0.0.tgz(r-4.3-emscripten)
CustomerScoringMetrics.pdf |CustomerScoringMetrics.html✨
CustomerScoringMetrics/json (API)
| # Install 'CustomerScoringMetrics' in R: |
| install.packages('CustomerScoringMetrics', repos = c('https://koendebock.r-universe.dev', 'https://cloud.r-project.org')) |
- response - Response data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:09f407d8ba. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 16 2024 |
| R-4.5-win | OK | Nov 16 2024 |
| R-4.5-linux | OK | Nov 16 2024 |
| R-4.4-win | OK | Nov 16 2024 |
| R-4.4-mac | OK | Nov 16 2024 |
| R-4.3-win | OK | Nov 16 2024 |
| R-4.3-mac | OK | Nov 16 2024 |
Exports:checkDepVectorconfMatrixMetricscumGainsChartcumGainsTablecutoffSensitivityPlotdynAccuracydynConfMatrixexpMisclassCostliftChartliftIndexliftTablemisclassCosttopDecileLift
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Perform check on the true class label vector | checkDepVector |
| Obtain several metrics based on the confusion matrix | confMatrixMetrics |
| Plot a cumulative gains chart | cumGainsChart |
| Calculates cumulative gains table | cumGainsTable |
| Plot a sensitivity plot for cutoff values | cutoffSensitivityPlot |
| Calculate accuracy | dynAccuracy |
| Calculate a confusion matrix | dynConfMatrix |
| Calculate expected misclassification cost | expMisclassCost |
| Generate a lift chart | liftChart |
| Calculate lift index | liftIndex |
| Calculate lift table | liftTable |
| Calculate misclassification cost | misclassCost |
| response data | response |
| Calculate top-decile lift | topDecileLift |
