View source: R/shortcut_functions.R
earf | R Documentation |
Calls adversarial_rf
, forde
and expct
.
For repeated application, it is faster to save outputs of adversarial_rf
and forde
and pass them via ...
or directly use expct
.
earf(x, ...)
x |
Input data. Integer variables are recoded as ordered factors with a warning. See Details. |
... |
Extra parameters to be passed to |
A one row data frame with values for all query variables.
Watson, D., Blesch, K., Kapar, J., & Wright, M. (2023). Adversarial random forests for density estimation and generative modeling. In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics, pp. 5357-5375.
arf
, adversarial_rf
, forde
, expct
# What is the expected values of each feature?
earf(iris)
#' # What is the expected values of Sepal.Length?
earf(iris, query = "Sepal.Length")
# What if we condition on Species = "setosa"?
earf(iris, query = "Sepal.Length", evidence = data.frame(Species = "setosa"))
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