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)