= Elastic net regularization
{wiki=Elastic_net_regularization}
Elastic Net regularization is a machine learning technique used to enhance the performance of linear regression models by addressing the problems of multicollinearity and overfitting. It combines two types of regularization techniques: Lasso (L1) and Ridge (L2) regularization. \#\#\# Key Components: 1. **Lasso Regularization (L1)**: - Adds a penalty equal to the absolute value of the coefficients (weights) to the loss function.
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