Model Interpretation Trend 2026

Model interpretation reveals how machine learning models make decisions by analyzing input-output relationships. It helps data scientists debug models, ensures regulatory compliance for financial and healthcare industries, and builds user trust. Techniques like feature importance and SHAP values clarify predictions, enabling stakeholders to validate fairness and accuracy in critical applications.