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**CI is still failing on [Ubuntu_Atlas.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72259&view=logs&j=689a1c8f-ff4e-5689-1a1a-6fa551ae9eba)** (Nov 22, 2024)
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Scikit-learn test for Ridge regression "test_ridge_cv_individual_penalties" shows the difference between the regression coefficients of scikit-learn and daal4py on small datasets, for multi-target pro…
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Train the lass regression model:
1. pull from the branch:
2. find the folder in …
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ll_regression_forest and predict.ll_regression_forest give the option to use a "covariance-standardized ridge penalty" in the splitting step (via ll.split.weight.penalty) and / or the prediciton step …
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Hello,
I would like to know if is it possible to pass a custum loss to the model ?
I guess the basic Loss is a Ridge Regression here, no.
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It seems to me that there is no regularized linear regression among the available algorithms, which are useful in my experience.
I can try to add [Ridge](https://scikit-learn.org/stable/modules/gen…
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Ridge regression is the most general algorithm for regression. It generalises all the regression methods implemented in this library as the problem of finding W such that the error e = (|| y-Wx ||) i…
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Currently, it only has "mae" for regression, "mse" and "ridge" are needed at least.
``` Python
def to_bigdl_metric(metric):
metric = metric.lower()
if metric == "accuracy" or metric == "ac…