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[BUG] Local v1 Affiliation Matching Test Failing #287

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adambuttrick opened this issue Jan 2, 2025 · 1 comment
Open

[BUG] Local v1 Affiliation Matching Test Failing #287

adambuttrick opened this issue Jan 2, 2025 · 1 comment
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bug Something is not working as defined

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@adambuttrick
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Version
v1

Describe the bug
@JeremyBrent reported on ror-community/ror-api#125 that ROR API test suite running in a local instance is failing due to accuracy falling below the minimum threshold in the affiliation matching test. The test test_matching in tests_matching_v1.py is failing with current accuracy at 0.762 (confidence interval: 0.736-0.788).

To Reproduce

  1. Set up local ROR API development environment
  2. Run the test suite
  3. Observe failure in rorapi.tests.tests_functional.tests_matching_v1.AffiliationMatchingTestCase

Expected behavior
The affiliation matching test should pass by meeting or exceeding the minimum accuracy threshold defined in ACCURACY_MIN.

Additional context
Full error trace:

======================================================================
FAIL: test_matching (rorapi.tests.tests_functional.tests_matching_v1.AffiliationMatchingTestCase)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/app/webapp/rorapi/tests/tests_functional/tests_matching_v1.py", line 53, in test_matching
    self.assertTrue(accuracy >= ACCURACY_MIN)
AssertionError: False is not true

Their logs show accuracy is:

  • Accuracy: 0.762
  • Confidence Interval: (0.736, 0.788)
@adambuttrick adambuttrick added the bug Something is not working as defined label Jan 2, 2025
@JeremyBrent
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Thanks for putting this together @adambuttrick 👍

To add one more detail, I updated ACCURACY_MIN, PRECISION_MIN & RECALL_MIN to 0 so it would run through. The metrics can be seen below:

Accuracy: 0.762 (0.7356054625748849, 0.7883945374251151)
Precision: 0.943217665615142 (0.9252034213795473, 0.9612319098507367)
Recall: 0.6651835372636262 (0.6343344447304241, 0.6960326297968283)

It looks like the model has good precision, but suffers on recall. Hope that helps!

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