zhengruifeng commented on a change in pull request #32124:
URL: https://github.com/apache/spark/pull/32124#discussion_r613816728
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File path: python/pyspark/ml/tests/test_training_summary.py
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@@ -223,12 +223,12 @@ def test_linear_svc_summary(self):
self.assertTrue(isinstance(s.precisionByThreshold, DataFrame))
self.assertTrue(isinstance(s.recallByThreshold, DataFrame))
print(s.weightedTruePositiveRate)
- self.assertAlmostEqual(s.weightedTruePositiveRate, 0.5, 2)
- self.assertAlmostEqual(s.weightedFalsePositiveRate, 0.5, 2)
- self.assertAlmostEqual(s.weightedRecall, 0.5, 2)
- self.assertAlmostEqual(s.weightedPrecision, 0.25, 2)
- self.assertAlmostEqual(s.weightedFMeasure(), 0.3333333333333333, 2)
- self.assertAlmostEqual(s.weightedFMeasure(1.0), 0.3333333333333333, 2)
+ self.assertAlmostEqual(s.weightedTruePositiveRate, 1.0, 2)
+ self.assertAlmostEqual(s.weightedFalsePositiveRate, 0.0, 2)
+ self.assertAlmostEqual(s.weightedRecall, 1.0, 2)
+ self.assertAlmostEqual(s.weightedPrecision, 1.0, 2)
+ self.assertAlmostEqual(s.weightedFMeasure(), 1.0, 2)
+ self.assertAlmostEqual(s.weightedFMeasure(1.0), 1.0, 2)
Review comment:
this test used dataset of only 2 instances, which seems unreliable.
But the new solution has better metrics (weightedFMeasure 0.5 -> 1.0)
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