Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/16774#discussion_r103045855
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala ---
@@ -121,6 +121,33 @@ class CrossValidatorSuite
}
}
+ test("cross validation with parallel evaluation") {
+ val lr = new LogisticRegression
+ val lrParamMaps = new ParamGridBuilder()
+ .addGrid(lr.regParam, Array(0.001, 1000.0))
+ .addGrid(lr.maxIter, Array(0, 3))
+ .build()
+ val eval = new BinaryClassificationEvaluator
+ val cv = new CrossValidator()
+ .setEstimator(lr)
+ .setEstimatorParamMaps(lrParamMaps)
+ .setEvaluator(eval)
+ .setNumFolds(2)
+ .setNumParallelEval(1)
+ val cvSerialModel = cv.fit(dataset)
+ cv.setNumParallelEval(2)
--- End diff --
Yes, the models could now be evaluated in a different order, but the end
result of returning the best model would be deterministic and shouldn't ever
change.
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