Bagging-FIGS: Ensemble of FIGS Models

bagging_figs() fits an ensemble of FIGS models using bootstrap resampling to increase stability and predictive performance on noisy datasets.

Usage

bagging_figs(
  formula,
  data,
  n_estimators = 10,
  max_splits = 6,
  min_n = 5,
  mode = "regression",
  na_method = c("omit", "mia"),
  ...
)

Arguments

formula

A formula.

data

A data frame.

n_estimators

Integer. Number of bootstrap FIGS models to train. Default is 10.

max_splits

Integer. Maximum splits per individual FIGS model. Default is 6.

min_n

Integer. Minimum node size. Default is 5.

mode

Character. "regression" or "classification"; classification supports two-class outcomes only.

na_method

Character. "omit" or "mia", passed to every member fit; see figs().

...

Additional arguments passed to figs().

Value

An object of class bagging_figs_fit.

Examples

set.seed(42)
df <- data.frame(x1 = rnorm(50), x2 = rnorm(50), y = rnorm(50))
bag_fit <- bagging_figs(y ~ x1 + x2, data = df, n_estimators = 3)