[MRG] Ensure that classification metrics support string label #2170
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Damn, this works well on my laptop. |
| def test_classification_report_multiclass_with_string_label(): | ||
| y_true, y_pred, _ = make_prediction(binary=False) | ||
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| y_true = y_true.astype(np.str) |
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Here's the bug: this produces an array of dtype='|S1' so the labels all get truncated to a single char. I'm on it.
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Ready for reviews! |
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| avg / total 0.62 0.61 0.56 75 |
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This was written twice
# print classification report with label detection
expected_report = """\
precision recall f1-score support
0 0.82 0.92 0.87 25
1 0.56 0.17 0.26 30
2 0.47 0.90 0.62 20
avg / total 0.62 0.61 0.56 75
"""
expected_report = """\
precision recall f1-score support
0 0.83 0.79 0.81 24
1 0.33 0.10 0.15 31
2 0.42 0.90 0.57 20
avg / total 0.51 0.53 0.47 75
"""The first expected report is erased by the second one.
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LGTM +1 |
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Should fix #1989 |
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Looks good to me as well be this branch require a rebase / conflicts fix before being able to merge. |
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@arjoly do you want to rebase or should I? |
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I'll do it |
Also found a faulty format op in the error handling.
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@amueller rebased on top of master |
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fail ;) |
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Hope it will good now. |
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@amueller it works ;-) |
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merged by rebase. Thanks a lot! |
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Since most estimators accept string as input, I make sure that most metrics will do.
This pr doesn't include metrics with y_score.
This should fix #2168, #1989