dynfeature (version 1.0.1)

fi_ranger_rf_lite: Feature Importance methods

Description

Feature Importance methods

Usage

fi_ranger_rf_lite(
  num_trees = 2000,
  num_variables_per_split = 50,
  num_samples_per_tree = 250,
  min_node_size = 20,
  ...
)
fi_ranger_rf(...)
fi_caret(caret_method, ...)
fi_ranger_rf_tiny(
  num_trees = 100,
  num_variables_per_split = 50,
  num_samples_per_tree = 250,
  min_node_size = 20,
  ...
)

Value

A list containing a helper function for calling a feature importance function.

Arguments

num_trees

(fi_ranger_rf_lite) The number of trees to use

num_variables_per_split

(fi_ranger_rf_lite) The number of variables to sample per split

num_samples_per_tree

(fi_ranger_rf_lite) The number of samples to bootstrap per split

min_node_size

(fi_ranger_rf_lite) The minimum node size, no split will be made if the node size is less than this value.

...

Extra parameters to pass onto the underlying feature importance function.

caret_method

(fi_caret) Which caret method to use for feature importance.

Examples

library(dynwrap)
data(example_trajectory)

calculate_overall_feature_importance(example_trajectory, fi_method = fi_ranger_rf())