OneVsOneClassifier: added an example to the documentation #16700
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glemaitre
reviewed
Mar 16, 2020
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@glemaitre I have added the requested changes |
adrinjalali
approved these changes
Mar 16, 2020
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.
glemaitre
approved these changes
May 12, 2020
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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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The to do list in issue #3846 mentioned that the
OneVsOneClassifierclassifier 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.