There are mainly two types of regularization techniques, which are given below:
• Ridge regression is mostly used to reduce the overfitting in the model, and it includes all the features present in the model. It reduces the complexity of the model by shrinking the coefficients.
• Lasso regression helps to reduce the overfitting in the model as well as feature selection.
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