Fix bug default marking of unlabeled data #20494
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Implement `unlabeled_mark` - a way for user to specify the way they mark unlabeled data, which also fix the bug described in issue scikit-learn#17951 Close: scikit-learn#17951
glemaitre
reviewed
Jul 21, 2021
| @@ -97,6 +97,15 @@ class BaseLabelPropagation(ClassifierMixin, BaseEstimator, metaclass=ABCMeta): | |||
| tol : float, default=1e-3 | |||
| Convergence tolerance: threshold to consider the system at steady | |||
| state. | |||
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| unlabeled_mark: {-1, 'unk'} or custom value, default=-1 | |||
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I assume that it would be better to accept a list with the potential value to be considered as unlabeled.
It looks like something similar to what we are using for the detection of the missing value.
We can also accept a single item that we can wrap in a list.
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Hi @glemaitre, sorry for the late reply. I can certainly add the list for |
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Reference Issues/PRs
Fixes #17951
What does this implement/fix? Explain your changes.
Implement
unlabeled_markas a parameter for BaseLabelPropagation.This is a way for user to specify the way that they mark unlabeled data,
which also fix the problem of described in issue #17951
Any other comments?
Thank you for reviewing this PR, if anything arise, please send me an email to
trantrikien239@gmail.com