SplitUplift {tools4uplift} | R Documentation |
Split data with respect to uplift distribution
Description
Split a dataset into training and validation subsets with respect to the uplift sample distribution.
Usage
SplitUplift(data, p, group)
Arguments
data |
a data frame of interest that contains at least the response and the treatment variables. |
p |
The desired sample size. p is a value between 0 and 1 expressed as a decimal, it is set to be proportional to the number of observations per group. |
group |
Your grouping variables. Generally, for uplift modelling, this should be a vector of treatment and response variables names, e.g. c("treat", "y"). |
Value
train |
a training data frame of p percent |
valid |
a validation data frame of 1-p percent |
Author(s)
Mouloud Belbahri
References
Belbahri, M., Murua, A., Gandouet, O., and Partovi Nia, V. (2019) Uplift Regression, <https://dms.umontreal.ca/~murua/research/UpliftRegression.pdf>
Examples
library(tools4uplift)
data("SimUplift")
split <- SplitUplift(SimUplift, 0.8, c("treat", "y"))
train <- split[[1]]
valid <- split[[2]]
[Package tools4uplift version 1.0.0 Index]