Difference between Ridge and LASSO and their geometric interpretation.

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Accepted Answer

Ridge and LASSO are regularization techniques used in linear regression to prevent overfitting.

Ridge adds a penalty term to the sum of squared errors, which shrinks the coefficients towards zero but doesn't set them exactly to zero.
LASSO adds a penalty term to the absolute value of the coefficients, which can set some of them exactly to zero.
The geometric interpretation of Ridge is that it adds a constraint to the size of the coefficients, which shrinks them towards the origin.
The geometric interpretation of LASSO is that it adds a constraint to the sum of the absolute values of the coefficients, which can lead to some of them being exactly zero.
Ridge is useful when all the features are important, while LASSO is useful when some of the features are irrelevant and can be eliminated.
Both Ridge and LASSO can be used to perform feature selection and reduce the complexity of the model.

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