The Ridge Regression is a regularized version of a Linear Regression. The Ridge Regression enables the machine learning algorithms to not only fit the data but also to keep weights of the model as small as possible.

It is quite familiar with the cost function that is used while training to be different from the performance measures that are used for testing. Apart from the Regularization, another reason for this difference is that a proper training data cost function should have optimization friendly derivatives. In contrast, the performance measures that are used for testing should be close as possible as the final objective.

Also, Read: Machine Translation Model using Neural Networks.

It is essential to scale the data by using Standard Scaler before using Ridge Regression, as it is sensitive to the scale of the input features. Now let’s go through the Ridge Regression algorithm to understand how to regularize a Liner Model using a Ridge algorithm.

#by aman kharwal #python #machine-learning #data-science