Ridge and lasso regression

Ridge and lasso regression are supervised linear regression ML algorithms. Both of these algorithms aim at reducing model complexity and prevent overfitting. When there is a large number of features or variables in a training dataset, the model built by ML generally tends to be complex.

Characteristics of ridge regression

The key characteristics of ridge regression are as follows:

• Coefficient shrinkage: This helps in reducing model complexity
• Regularization: This adds information to prevent overfitting

Characteristics of lasso regression

Lasso...