Feature importances: Revision history

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18 March 2023

  • curprev 19:0219:02, 18 March 2023‎ Walle talk contribs‎ 4,051 bytes +4,051‎ Created page with "{{see also|Machine learning terms}} ==Introduction== Feature importances refer to the quantification of the relative contribution of each feature (or input variable) to the overall predictive performance of a machine learning model. Identifying and understanding the importance of features in a model can aid in model interpretation, feature selection, and ultimately, the improvement of model performance. Various techniques have been proposed to assess the significance..."
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