Model Interpretation

Model interpretation involves understanding how a machine learning model makes its decisions or predictions. It helps identify which features or data points influence the outcomes most significantly. By interpreting the model, we can ensure it behaves fairly, reliably, and transparently, making it easier to trust and improve. This process is essential across industries like healthcare, finance, and marketing, where understanding the reasons behind decisions can impact ethical considerations, regulatory compliance, and strategic planning. Overall, model interpretation makes complex algorithms clearer and more accessible, fostering confidence and responsible use.