model-explainer
Model Explainer
Overview
Makes black-box models interpretable. Explains why models make specific predictions, which features matter most, and how features interact. Critical for trust, debugging, and regulatory compliance.
Why Explainability Matters
- Trust: Stakeholders trust models they understand
- Debugging: Find model weaknesses and biases
- Compliance: GDPR, fair lending laws require explanations
- Improvement: Understand what to improve
- Safety: Detect when model might fail
Explanation Types
1. Global Explanations (Model-Level)
Feature Importance:
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