[ENH] Added sample_weight parameter#631
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ParamThakkar123 wants to merge 1 commit intosktime:mainfrom
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Nov 17, 2025
| np.vstack((y_pred[:i, :], y_pred[i + 1 :, :])), # noqa | ||
| self.multioutput, | ||
| **kwargs, | ||
| if isinstance(y_true, np.ndarray): |
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could you explain why the case distinction based on if isinstance(y_true, np.ndarray)? How does introducing sample_weight change this?
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The isinstance(y_true, np.ndarray) branch exists because the code removes the i-th sample using NumPy slicing/stacking which only works reliably for plain NumPy arrays. Adding sample_weight requires removing the same sample from the weight array/Series with the same method (np.delete/mask for NumPy or .iloc/.drop for pandas) to keep alignment, otherwise metrics might become incorrect?
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- what are the two cases that this tries to cover, exactly?
- why do we not need to do this before your change?
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Reference Issues/PRs
Fixes #369
What does this implement/fix? Explain your changes.
This PR adds a new
sample_weightparameter to metrics as described in #369Does your contribution introduce a new dependency? If yes, which one?
What should a reviewer concentrate their feedback on?
Did you add any tests for the change?
Any other comments?
I am open to suggestions to change this PR according to the reviewers.
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