Do you know what regularization is and why it is useful?
Submitted by: MuhammadRegularization is the process of adding tunning parameter to a model to induce smoothness in order to prevent overfitting. This is most often done by adding a constant multiple to an existing weight vector. This constant is often the L1(Lasso) or L2(ridge). The model predictions should then minimize the loss function calculated on the regularized training set.
Submitted by: Muhammad
Submitted by: Muhammad
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