Walle
Created page with "{{see also|Machine learning terms}} ==Permutation Variable Importance== Permutation Variable Importance (PVI) is a technique used in machine learning to evaluate the importance of individual features in a predictive model. This method estimates the impact of a specific feature on the model's predictive accuracy by assessing the changes in model performance when the values of that feature are permuted randomly. The main advantage of PVI is its applicability to a wide..."
