Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/18428#discussion_r125175225
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala ---
@@ -156,6 +156,52 @@ class CrossValidatorSuite
CrossValidatorSuite.compareParamMaps(cv.getEstimatorParamMaps,
cv2.getEstimatorParamMaps)
}
+ test("read/write: CrossValidator with nested estimator") {
+ val ova = new OneVsRest().setClassifier(new LogisticRegression)
+ val evaluator = new MulticlassClassificationEvaluator()
+ .setMetricName("accuracy")
+ val classifier1 = new LogisticRegression().setRegParam(2.0)
+ val classifier2 = new LogisticRegression().setRegParam(3.0)
+ // params that are not JSON serializable must inherit from Params
+ val paramMaps = new ParamGridBuilder()
+ .addGrid(ova.classifier, Array(classifier1, classifier2))
+ .build()
+ val cv = new CrossValidator()
+ .setEstimator(ova)
+ .setEvaluator(evaluator)
+ .setNumFolds(20)
+ .setEstimatorParamMaps(paramMaps)
+
+ val cv2 = testDefaultReadWrite(cv, testParams = false)
+
+ assert(cv.uid === cv2.uid)
+ assert(cv.getNumFolds === cv2.getNumFolds)
+ assert(cv.getSeed === cv2.getSeed)
+
+
assert(cv2.getEvaluator.isInstanceOf[MulticlassClassificationEvaluator])
+ val evaluator2 =
cv2.getEvaluator.asInstanceOf[MulticlassClassificationEvaluator]
+ assert(evaluator.uid === evaluator2.uid)
+ assert(evaluator.getMetricName === evaluator2.getMetricName)
+
+ cv2.getEstimator match {
+ case ova2: OneVsRest =>
+ assert(ova.uid === ova2.uid)
+ val classifier = ova2.getClassifier
+ classifier match {
+ case lr: LogisticRegression =>
+
assert(ova.getClassifier.asInstanceOf[LogisticRegression].getMaxIter
+ === lr.asInstanceOf[LogisticRegression].getMaxIter)
--- End diff --
lr is already of type LogisticRegression (no need to cast)
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