Principle:Interpretml Interpret Feature Group Importance
Metadata
| Field | Value |
|---|---|
| Sources | Interpretml_Interpret |
| Domains | Machine_Learning, Interpretability |
| Updated | 2026-02-07 |
Overview
Feature group importance computes the collective contribution of semantically related groups of features or terms in a fitted EBM model.
Description
The group importance module provides utility functions to compute and visualize how sets of related features collectively contribute to model predictions in an Explainable Boosting Machine. Rather than examining individual feature importances, this allows users to define meaningful groups of features (e.g., all demographic features, all financial features) and compute aggregate importance scores for each group. This is useful for understanding which domains of features have the most influence on the model.
Usage
Use feature group importance when you want to understand the collective impact of semantically related feature groups in a fitted EBM, rather than examining individual feature importances.