Editing Bayesian Ridge sample weight for y_predict std #30433
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Reference Issues/PRs
Fixes #24313What does this implement/fix? Explain your changes.
This fixes the effect of uniform sample weights on the standard deviation of y_predict in the Bayesian Ridge Regression model. The sample weights have been normalized by dividing them by their mean. This ensured that the absolute scale of uniform weights did not affect the calculations, preserving only their relative importance.
Before:
if sample_weight is not None: sample_weight = _check_sample_weight(sample_weight, X, dtype=dtype)After:
if sample_weight is not None: sample_weight = _check_sample_weight(sample_weight, X, dtype=dtype) sample_weight = sample_weight / np.mean(sample_weight)Any other comments?