scientific-feature-importance
CommunityExplain ML models via feature importance.
Data & Analytics#visualization#machine-learning#explainability#feature-importance#multi-target#permutation-importance#PDP
Authornahisaho
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill quantifies the contribution of individual features to machine learning model predictions, enabling clearer model explanations by combining Tree-based Feature Importance (MDI) and Permutation Importance.
Core Features & Use Cases
- Tree-based Feature Importance (MDI) to identify influential features across models.
- Permutation Importance to validate feature impact with model-agnostic assessment.
- Multi-target importance panels and partial dependence plots to compare across targets and inspect feature effects.
- Output CSVs and figures for documentation and reporting.
Quick Start
Train a model on your dataset and run the provided analysis functions to generate feature-importance figures and the results table.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: scientific-feature-importance Download link: https://github.com/nahisaho/satori/archive/main.zip#scientific-feature-importance Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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