| liftTable {CustomerScoringMetrics} | R Documentation | 
Calculate lift table
Description
Calculates a lift table, showing for different percentiles of predicted scores how much more the characteristic or action of interest occurs than for the overall sample.
Usage
liftTable(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%). | 
Value
A lift table.
Author(s)
Koen W. De Bock, kdebock@audencia.com
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.
See Also
topDecileLift, liftIndex, liftChart
Examples
## Load response modeling predictions
data("response")
## Apply liftTable function to obtain lift table for test sample results and print
## results
lt<-liftTable(response$test[,2],response$test[,1])
print(lt)
[Package CustomerScoringMetrics version 1.0.0 Index]