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OneVsOneClassifier: added an example to the documentation #16700
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OneVsOneClassifier: added an example to the documentation #16700
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A couple of changes but it looks good
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@glemaitre I have added the requested changes |
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Otherwise LGTM, thanks @j0rd1smit
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sklearn/multiclass.py
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8000 | >>> clf.predict(X_test) | |
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, | ||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, | ||
0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, | ||
1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, | ||
1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, | ||
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, | ||
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]) |
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I think showing the output of even only one input i.e. X_test[0, :]
should be enough.
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@j0rd1smit I just pushed a commit with the suggestion of @adrinjalali and I will merge when the CIs are happy. Thanks for your work. |
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adrinjalali
glemaitre
Successfully merging this pull request may close these issues.
The to do list in issue #3846 mentioned that the
OneVsOneClassifier
classifier needed an example in its documentation. I saw the was already an example in the user guide so I added this example to the documentation.