Description Usage Arguments Value Author(s) References See Also Examples
Univariate optimal partitionning for Uplift Models. The algorithm quantizes a single variable into bins with significantly different observed uplift.
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data |
a data frame containing the treatment, the outcome and the predictor to quantize. |
treat |
name of a binary (numeric) vector representing the treatment assignment (coded as 0/1). |
outcome |
name of a binary response (numeric) vector (coded as 0/1). |
x |
name of the explanatory variable to quantize. |
n.split |
number of splits to test at each node. For continuous explanatory variables only (must be > 0). If n.split = 10, the test will be executed at each decile of the variable. |
alpha |
significance level of the statistical test (must be between 0 and 1). |
n.min |
minimum number of observations per child node. |
out.tree |
Descriptive statistics for the different nodes of the tree |
Mouloud Belbahri
Belbahri, M., Murua, A., Gandouet, O., and Partovi Nia, V. (2021) Uplift Regression : The R Package tools4uplift, <https://arxiv.org/pdf/1901.10867.pdf>
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