Support binary case #215
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Support binary case #215
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ejm714
reviewed
Aug 22, 2022
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Looks like the failing test is Seems like we need to either install |
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Looks like this was broken a few days ago: https://github.com/drivendataorg/zamba/runs/7904627719?check_suite_focus=true |
Codecov Report
@@ Coverage Diff @@
## master #215 +/- ##
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Coverage 86.9% 87.0%
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Files 29 29
Lines 1910 1918 +8
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+ Hits 1661 1669 +8
Misses 249 249
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ejm714
approved these changes
Aug 23, 2022
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LGTM, @AllenDowney you can merge once the tests finish passing
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Picking up where #200 left off...
If a user provides only two labels, we check that they are mutually exclusive and, if so, train the binary model. We log which column we're keeping.
Outstanding:
Note: I gave this a quick try on a dataset of 100 videos balanced evenly between blank and non blank and we indeed see some learning.
Some downsides to the binary case is that these metrics can look misleading when the class are imbalanced. Not sure the best way to warn users about that. If users provide highly imbalanced data, models may learn problematically to only predict the default class, but I suppose that is the same in the multilabel case.