empChurn: empChurn

In EMP: Expected Maximum Profit Classification Performance Measure

empChurn

Description

Estimates the EMP for customer churn prediction, considering constant CLV and a given cost of contact f and retention offer d.

Usage

empChurn(scores, classes, alpha = 6, 
beta = 14, clv = 200, d = 10, f = 1)

Arguments

scores	A vector of predicted probabilities.
classes	A vector of true binary class labels.
alpha	Alpha parameter of unimodel beta distribution.
beta	Beta parameter of unimodel beta distribution.
clv	Constant CLV per retained customer.
d	Constant cost of retention offer.
f	Constant cost of contact.

Value

An EMP object with four components.

MP	The Maximum Profit of the ROC curve at MPfrac cutoff.
MPfrac	The percentage of cases that should be excluded, that is, the percentual cutoff at MP profit.
EMP	The Expected Maximum Profit of the ROC curve at EMPfrac cutoff.
EMPfrac	The percentage of cases that should be excluded, that is, the percentual cutoff at EMP profit.

Author(s)

Cristian Bravo, Seppe vanden Broucke and Thomas Verbraken.

References

Verbraken, T., Wouter, V. and Baesens, B. (2013). A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models. Knowledge and Data Engineering, IEEE Transactions on. 25 (5): 961-973. Available Online: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1109/TKDE.2012.50")} Verbraken, T., Bravo, C., Weber, R. and Baesens, B. (2014). Development and application of consumer credit scoring models using profit-based classification measures. European Journal of Operational Research. 238 (2): 505 - 513. Available Online: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.ejor.2014.04.001")}

See Also

See Also empChurn, prediction.

Examples

# Construct artificial probability scores and true class labels
score.ex <- runif(1000, 0, 1)
class.ex <- unlist(lapply(score.ex, function(x){rbinom(1,1,x)}))

# Calculate EMP measures for customer churn prediction
empChurn(score.ex, class.ex)

# Calculate EMP measures for customer churn prediction with
# lower clv and higher costs
empChurn(score.ex, class.ex, clv = 100, d = 30, f = 5)

EMP documentation built on June 8, 2025, 1:52 p.m.