Explainability of a Model In Image Classification
Explainability refers to the ability to understand and interpret the decisions and behavior of a machine learning (ML) model. It involves gaining insights into how and why the model arrives at its predictions or classifications. Explainability is crucial for building trust, ensuring fairness, and meeting regulatory and ethical requirements in