feature.selection: Selects the top features with highest weighted mean shap...

In shapley: Weighted Mean SHAP and CI for Robust Feature Assessment in ML Grid

Selects the top features with highest weighted mean shap values based on the specified criteria

Description

This function specifies the top features and prepares the data for plotting SHAP contributions for each row, or summary of absolute SHAP contributions for each feature.

Usage

feature.selection(
  shapley,
  method = "mean",
  cutoff = 0,
  top_n_features = NULL,
  features = NULL
)

Arguments

shapley	shapley object
method	Character. The column name in summaryShaps used for feature selection. Default is "mean", which selects important features which have weighted mean shap ratio (WMSHAP) higher than the specified cutoff. Other alternative is "lowerCI", which selects features which their lower bound of confidence interval is higher than the cutoff.
cutoff	numeric, specifying the cutoff for the method used for selecting the top features. the default is zero, which means that all features with the "method" criteria above zero will be selected.
top_n_features	integer. if specified, the top n features with the highest weighted SHAP values will be selected, overrullung the 'cutoff' and 'method' arguments.
features	character vector, specifying the feature to be plotted.

Value

normalized numeric vector

Author(s)

E. F. Haghish

shapley documentation built on April 12, 2025, 2:16 a.m.