liftChart: Generate a lift chart

In CustomerScoringMetrics: Evaluation Metrics for Customer Scoring Models Depending on Binary Classifiers

Description

Visualize lift through a lift chart.

Usage

liftChart(predTest, depTest, resolution = 1/10)

Arguments

predTest	Vector with predictions (real-valued or discrete)
depTest	Vector with true class labels
resolution	Value for the determination of percentile intervals. Default 1/10 (10%).

Author(s)

Koen W. De Bock, [e-mail]

References

Berry, M.J.A. and Linoff, G.S. (2004): "Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management - Second Edition". John Wiley & Sons.

Blattberg, R.C., Kim, B.D. and Neslin, S.A. (2008): "Database Marketing: Analyzing and Managing Customers". Springer.

See Also

topDecileLift, liftIndex, liftChart

Examples

## Load response modeling predictions
data("response")
## Apply liftChart function to visualize lift table results
liftChart(response$test[,2],response$test[,1])

CustomerScoringMetrics documentation built on May 2, 2019, 5:17 a.m.