View source: R/shortcut_functions.R
| darf | R Documentation |
Calls adversarial_rf, forde and lik.
For repeated application, it is faster to save outputs of adversarial_rf
and forde and pass them via ... or directly use lik.
darf(x, query = NULL, ...)
x |
Input data. Integer variables are recoded as ordered factors with a warning. See Details. |
query |
Data frame of samples, optionally comprising just a subset of
training features. See Details of |
... |
Extra parameters to be passed to |
A vector of likelihoods, optionally on the log scale. A dataset of
n_synth synthetic samples or of nrow(x) synthetic
samples if n_synth is undefined.
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, forge
# Estimate log-likelihoods
ll <- darf(iris)
# Partial evidence query
ll <- darf(iris, query = iris[1, 1:3])
# Condition on Species = "setosa"
ll <- darf(iris, query = iris[1, 1:3], evidence = data.frame(Species = "setosa"))
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