Permutation variable importances: Revision history

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18 March 2023

  • curprev 21:5521:55, 18 March 2023‎ Walle talk contribs‎ 3,580 bytes +3,580‎ 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..."
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