Problem 55185. Ridge regularized linear regression
Given a predictor data matrix X of size , target variable vector y of size and a shrinkage factor λ (scalar) (ridge regularization), write the function to compute linear regression model coefficients β to model the data. The data has n observations, p predictor variables in the X matrix
The model is defines as: where sigma is gaussian noise.
(Hint: search on google for closed form solution of a linear regression problem)
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2 Comments
ChrisR
on 14 Jul 2022
Yuvraj, this problem looks interesting, and I was looking forward to learning about ridge regularization. I suggest that you remove the code from the function template: you are giving us the answer! Also, several Cody players have recommended at least four tests to discourage lookup table solutions and other cheats.
Christian Schröder
on 12 Nov 2022
The test suite's incorrect: the matrix inversion in the ridge estimator is missing.
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