FEA Add a basic RidgeCV estimator - #8349
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/ok to test c9b85f1 |
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Bigger question: do we even need this in cuml itself? We could array-API'ify the one in scikit-learn instead. |
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This adds the
RidgeCVestimator. It provides ridge regression with built-in cross-validation. Modelled on the scikit-learn class https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeCV.html.From the benchmarking I've done
RidgeCV(alphas=[1.])keeps up withRidgein terms of performance. So implementing this in cupy seems fine instead of adding overhead by going to c++The benchmarking related code is an effort to follow the pattern of already existing things. I didnt try to run the benchmark suite though.
Things this doesn't implement:
XI used AI for research/understanding, generating code and tests. Then cleaned up after that.
Towards #7824