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What is Lasso and Ridge Regression Overview about?

The document discusses different regularization techniques for machine learning models. It describes Lasso (L1) regularization, which adds a penalty based on the absolute value of weights, and Ridge (L2) regularization, which adds a penalty based on the squared weights. Lasso regularization can drive some weights to exactly zero, while Ridge regularization only reduces weights. Cross-validation is also discussed as a method to evaluate models on limited data and estimate performance on unseen data.

Author

Ali

Language

EN