Metrics

Explainable metrics play a crucial role in achieving transparent and trustworthy outcomes of machine learning models. These metrics help in quantifying the ease of interpreting the results from explainability methods.

• Spread Metrics
  • Alpha Importance Score
  • Feature Spread Metric
• Order Cohesion Metrics
  • Position Parity
  • Rank Alignment
• Feature Permutation-Based Metric
  • Explainability Ease Score Metric
• Stability Metrics
  • Feature Stability
• Tree Based Metrics
  • What is a tree-based model?
  • Tree-Based Metrics