L1 regularization: Revision history

Diff selection: Mark the radio buttons of the revisions to compare and hit enter or the button at the bottom.
Legend: (cur) = difference with latest revision, (prev) = difference with preceding revision, m = minor edit.

18 March 2023

  • curprev 13:1113:11, 18 March 2023‎ Walle talk contribs‎ 3,011 bytes +3,011‎ Created page with "{{see also|Machine learning terms}} ==L1 Regularization in Machine Learning== L1 regularization, also known as Lasso regularization or L1 norm, is a widely used regularization technique in machine learning and statistical modeling to prevent overfitting and enhance the generalization of the model. It achieves this by introducing a penalty term in the optimization objective that encourages sparsity in the model parameters. ===Overview=== Regularization techniques are emp..."
Retrieved from "http:///wiki/L1_regularization"