Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/12767#discussion_r63535245
--- Diff: python/pyspark/ml/tests.py ---
@@ -594,17 +594,21 @@ def test_fit_minimize_metric(self):
iee = InducedErrorEstimator()
evaluator = RegressionEvaluator(metricName="rmse")
- grid = (ParamGridBuilder()
- .addGrid(iee.inducedError, [100.0, 0.0, 10000.0])
- .build())
+ grid = ParamGridBuilder() \
+ .addGrid(iee.inducedError, [100.0, 0.0, 10000.0]) \
+ .build()
tvs = TrainValidationSplit(estimator=iee, estimatorParamMaps=grid,
evaluator=evaluator)
tvsModel = tvs.fit(dataset)
bestModel = tvsModel.bestModel
bestModelMetric = evaluator.evaluate(bestModel.transform(dataset))
+ validationMetrics = tvsModel.validationMetrics
self.assertEqual(0.0, bestModel.getOrDefault('inducedError'),
"Best model should have zero induced error")
self.assertEqual(0.0, bestModelMetric, "Best model has RMSE of 0")
+ self.assertEqual(len(grid), len(validationMetrics),
+ "validationMetrics has the same size of grid
parameter")
+ self.assertEqual(bestModelMetric, min(validationMetrics))
--- End diff --
With @MLnick's previous comment in mind, my preference would be to instead
check:
`self.assertEqual(0.0, min(validationMetrics))`
That way we don't put in a check that is wrong in general, but correct
here. I don't feel too strongly about it, but since it's an easy fix and we
might save some future developer a bit of confusion then I think it's a good
idea. Same in the maximize version.
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