[SPARK-12810][PYSPARK] PySpark CrossValidatorModel should support avgMetrics

## What changes were proposed in this pull request?
support avgMetrics in CrossValidatorModel with Python
## How was this patch tested?
Doctest and `test_save_load` in `pyspark/ml/test.py`
[JIRA](https://issues.apache.org/jira/browse/SPARK-12810)

Author: Kai Jiang <jiangkai@gmail.com>

Closes #12464 from vectorijk/spark-12810.

1 files changed, 27 insertions, 0 deletions

diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py
index ebef656632..36cecd4682 100644
--- a/python/pyspark/ml/tests.py
+++ b/python/pyspark/ml/tests.py
@@ -466,6 +466,31 @@ class InducedErrorEstimator(Estimator, HasInducedError):
 
 class CrossValidatorTests(PySparkTestCase):
 
+    def test_copy(self):
+        sqlContext = SQLContext(self.sc)
+        dataset = sqlContext.createDataFrame([
+            (10, 10.0),
+            (50, 50.0),
+            (100, 100.0),
+            (500, 500.0)] * 10,
+            ["feature", "label"])
+
+        iee = InducedErrorEstimator()
+        evaluator = RegressionEvaluator(metricName="rmse")
+
+        grid = (ParamGridBuilder()
+                .addGrid(iee.inducedError, [100.0, 0.0, 10000.0])
+                .build())
+        cv = CrossValidator(estimator=iee, estimatorParamMaps=grid, evaluator=evaluator)
+        cvCopied = cv.copy()
+        self.assertEqual(cv.getEstimator().uid, cvCopied.getEstimator().uid)
+
+        cvModel = cv.fit(dataset)
+        cvModelCopied = cvModel.copy()
+        for index in range(len(cvModel.avgMetrics)):
+            self.assertTrue(abs(cvModel.avgMetrics[index] - cvModelCopied.avgMetrics[index])
+                            < 0.0001)
+
     def test_fit_minimize_metric(self):
         sqlContext = SQLContext(self.sc)
         dataset = sqlContext.createDataFrame([
@@ -539,6 +564,8 @@ class CrossValidatorTests(PySparkTestCase):
         cvModel.save(cvModelPath)
         loadedModel = CrossValidatorModel.load(cvModelPath)
         self.assertEqual(loadedModel.bestModel.uid, cvModel.bestModel.uid)
+        for index in range(len(loadedModel.avgMetrics)):
+            self.assertTrue(abs(loadedModel.avgMetrics[index] - cvModel.avgMetrics[index]) < 0.0001)
 
 
 class TrainValidationSplitTests(PySparkTestCase):