[MRG] Fix fetch_openml when ignore attributes are numeric #12330
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If all goes green LGTM. Not sure if it's worth adding a dataset to |
jnothman
reviewed
Oct 8, 2018
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Btw, should I add a note in the what's new doc? In 0.20 or 0.21? I could append it to the previous entry that was merged by #12246 |
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It can be a separate note in 0.20.1
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jnothman
approved these changes
Oct 9, 2018
| @@ -410,6 +410,25 @@ def test_fetch_openml_australian(monkeypatch, gzip_response): | |||
| ) | |||
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| @pytest.mark.parametrize('gzip_response', [True, False]) | |||
| def test_fetch_openml_adultcensus(monkeypatch, gzip_response): | |||
| # Check because of the numeric row attribute | |||
sklearn/datasets/openml.py
Outdated
| @@ -555,13 +567,12 @@ def fetch_openml(name=None, version='active', data_id=None, data_home=None, | |||
| arff = _download_data_arff(data_description['file_id'], return_sparse, | |||
| data_home) | |||
| arff_data = arff['data'] | |||
| # nominal attributes is a dict mapping from the attribute name to the | |||
| # possible values. Includes also the target column | |||
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Note however that the target is popped off below
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I left 10 observations in the dataset, making it to my opinion reasonably small. |
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regression test fails on master, whole data is 24k, looks good. |
jnothman
pushed a commit
to jnothman/scikit-learn
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Oct 15, 2018
…rn#12330) * modularized data column functionality * small bugfix * removes redundant line breaks * added some documentation on the added fn * added additional comment on advice of Nicholas Hug * added test case * merged master into branch, and added small comments by Joel * added doc item
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Fixes #12329
I modularized the function that determines per column whether it is a valid data column (opposed to a target or ignore attribute). This functionality was before (in slightly different manifestations) on 2 different places in the code. This simplifies the main function.
I did not add an additional unit test, as that would require packaging more openml files etc. Personally I think that the fact that the code is more modular and the bug is removed adds to the readability and quality of the code. Let me know if you think otherwise, I can of course add a unit test.