Solving Ridge Regression

Learn how to estimate the optimal parameters of ridge regression using the gradient-solving approach.

Ridge regression

Ridge regression or L2L_2-regularized linear regression is a type of linear regression problem where model coefficients are constrained to zero or near zero. Given XRN×dX \in \R^{N \times d} that denotes the set of NN dd-dimensional inputs and their corresponding true labels YRNY \in \R^N, the objective of ridge regression is given as follows:

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