How Can AI Models Be Made Interpretable and Explainable?

Akanksha20 Dec, 2024Education

Start with inherently interpretable models like linear regression, decision trees, or rule-based systems, which are easier to understand. Techniques like SHAP (Shapley Additive Explanations) or LIME (Local Interpretable Model-Agnostic Explanations) help identify which features contribute most to a model’s predictions. show how individual features impact predictions in complex models.