[SPARK-14306][ML][PYSPARK] PySpark ml.classification OneVsRest support export/import

## What changes were proposed in this pull request?

https://issues.apache.org/jira/browse/SPARK-14306

Add PySpark OneVsRest save/load supports.

## How was this patch tested?

Test with Python unit test.

Author: Xusen Yin <yinxusen@gmail.com>

Closes #12439 from yinxusen/SPARK-14306-0415.

1 files changed, 24 insertions, 1 deletions

diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py
index a7a9868bac..9d6ff47b54 100644
--- a/python/pyspark/ml/tests.py
+++ b/python/pyspark/ml/tests.py
@@ -43,7 +43,8 @@ import tempfile
 import numpy as np
 
 from pyspark.ml import Estimator, Model, Pipeline, PipelineModel, Transformer
-from pyspark.ml.classification import LogisticRegression, DecisionTreeClassifier, OneVsRest
+from pyspark.ml.classification import (
+    LogisticRegression, DecisionTreeClassifier, OneVsRest, OneVsRestModel)
 from pyspark.ml.clustering import KMeans
 from pyspark.ml.evaluation import BinaryClassificationEvaluator, RegressionEvaluator
 from pyspark.ml.feature import *
@@ -881,6 +882,28 @@ class OneVsRestTests(PySparkTestCase):
         output = model.transform(df)
         self.assertEqual(output.columns, ["label", "features", "prediction"])
 
+    def test_save_load(self):
+        temp_path = tempfile.mkdtemp()
+        sqlContext = SQLContext(self.sc)
+        df = sqlContext.createDataFrame([(0.0, Vectors.dense(1.0, 0.8)),
+                                         (1.0, Vectors.sparse(2, [], [])),
+                                         (2.0, Vectors.dense(0.5, 0.5))],
+                                        ["label", "features"])
+        lr = LogisticRegression(maxIter=5, regParam=0.01)
+        ovr = OneVsRest(classifier=lr)
+        model = ovr.fit(df)
+        ovrPath = temp_path + "/ovr"
+        ovr.save(ovrPath)
+        loadedOvr = OneVsRest.load(ovrPath)
+        self.assertEqual(loadedOvr.getFeaturesCol(), ovr.getFeaturesCol())
+        self.assertEqual(loadedOvr.getLabelCol(), ovr.getLabelCol())
+        self.assertEqual(loadedOvr.getClassifier().uid, ovr.getClassifier().uid)
+        modelPath = temp_path + "/ovrModel"
+        model.save(modelPath)
+        loadedModel = OneVsRestModel.load(modelPath)
+        for m, n in zip(model.models, loadedModel.models):
+            self.assertEqual(m.uid, n.uid)
+
 
 class HashingTFTest(PySparkTestCase):