scientific-explainable-ai
CommunityExplainable AI insights reveal model reasoning.
Authornahisaho
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Explainable AI (XAI) analysis visualizes and quantifies model predictions, helping researchers extract scientific insights and trust results.
Core Features & Use Cases
- Global explanations and feature importance using SHAP, LIME, and related methods to reveal overall model behavior.
- Local explanations for individual predictions with SHAP/LIME/Captum/InterpretML to justify decisions.
- Counterfactual explanations and fairness audits to assess robustness and regulatory readiness.
- Regulatory compliance alignment and audit-ready reporting for scientific workflows.
Quick Start
Run the XAI pipeline to generate global SHAP summaries, local explanations, counterfactual analyses, and fairness diagnostics.
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-explainable-ai Download link: https://github.com/nahisaho/satori/archive/main.zip#scientific-explainable-ai Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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