Shrinkage: Revision history

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18 March 2023

  • curprev 21:5621:56, 18 March 2023‎ Walle talk contribs‎ 2,960 bytes +2,960‎ Created page with "{{see also|Machine learning terms}} ==Introduction== '''Shrinkage''' in machine learning is a regularization technique that aims to prevent overfitting in statistical models by adding a constraint or penalty to the model's parameters. Shrinkage methods reduce the complexity of the model by pulling its coefficient estimates towards zero, leading to more robust and interpretable models. Popular shrinkage methods include Ridge Regression and Lasso Regression. ==Shrinka..."
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