Description Usage Arguments Value Author(s) References See Also Examples
View source: R/PerformanceUplift.R
Table of performance of an uplift model. This table is used in order to vizualise the performance of an uplift model and to compute the qini coefficient.
1 2 | PerformanceUplift(data, treat, outcome, prediction, nb.group = 10,
equal.intervals = TRUE, rank.precision = 2)
|
data |
a data frame containing the response, the treatment and predicted uplift. |
treat |
a binary (numeric) vector representing the treatment assignment (coded as 0/1). |
outcome |
a binary response (numeric) vector (coded as 0/1). |
prediction |
a predicted uplift (numeric) vector to sort the observations from highest to lowest uplift. |
nb.group |
if equal.intervals is set to true, the number of groups of equal observations in which to partition the data set to show results. |
equal.intervals |
flag for using equal intervals (with equal number of observations) or the true ranking quantiles which result in an unequal number of observations in each group. |
rank.precision |
precision for the ranking quantiles. Must be 1 or 2. If 1, the ranking quantiles will be rounded to the first decimal. If 2, to the second decimal. |
a table with descriptive statistics related to an uplift model estimator.
Mouloud Belbahri
Radcliffe, N. (2007). Using control groups to target on predicted lift: Building and assessing uplift models. Direct Marketing Analytics Journal, An Annual Publication from the Direct Marketing Association Analytics Council, pages 14-21.
Belbahri, M., Murua, A., Gandouet, O., and Partovi Nia, V. (2019) Uplift Regression, <https://dms.umontreal.ca/~murua/research/UpliftRegression.pdf>
1 2 3 4 5 6 7 8 9 10 | library(tools4uplift)
data("SimUplift")
model1 <- BinUplift2d(SimUplift, "X1", "X2", "treat", "y")
perf1 <- PerformanceUplift(data = model1, treat = "treat",
outcome = "y", prediction = "Uplift_X1_X2",
equal.intervals = TRUE, nb.group = 3)
print(perf1)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.