Add pipeline.should_skip_featurization flag #3849
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## main #3849 +/- ##
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+ Coverage 99.7% 99.7% +0.1%
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Files 344 344
Lines 36185 36190 +5
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+ Hits 36048 36053 +5
Misses 137 137
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eccabay
requested review from
jeremyliweishih,
christopherbunn and
chukarsten
jeremyliweishih
approved these changes
Nov 21, 2022
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| y = pd.Series(range(PERIODS)) | ||
| if problem_type == ProblemTypes.TIME_SERIES_BINARY: |
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can you add the parametrization for these problem types?
| assert pipeline.should_skip_featurization | ||
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| @patch( |
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do you think its cleaner to add the pipeline fitting logic to test_can_run_automl_for_time_series_with_exclude_featurizers and check after search is run? I think either works!
chukarsten
approved these changes
Nov 22, 2022
Merged
chukarsten
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Nov 29, 2022
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Fixes an issue where time series native estimators were double-featurizing during predict when featurization happens before running evalml