Problem 55185. Ridge regularized linear regression

Created by Yuvraj

Difficulty:Rate

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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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18 Solutions
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Last Solution submitted on May 03, 2024

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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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