Hi, I was looking at docs for Ridge regression and it states that it minimizes
||y - Xw||^2 + alpha*||w||^2 I would like to minimize the function ||y-Xw||^2 + ||Tx||^2, where T is a matrix, in order to impose certain properties on the solution vectors, but I haven't found any way to achieve that in scikit-learn. Is this type of regularisation supported in scikit-learn? More details on the ||Tx||^2 regularisation can be found here https://en.wikipedia.org/wiki/Tikhonov_regularization Best, David
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