Feature Importance

Feature Importance refers to techniques in machine learning models that quantify the degree of influence each feature has on the model's prediction outcomes. Its objective is to evaluate the importance of features to help understand the model's decision-making mechanism, optimize feature selection, and improve model performance. The application value lies in enhancing model interpretability, supporting business decisions, reducing data dimensions, and improving computational efficiency.