Repository: spark
Updated Branches:
  refs/heads/master bec0a9217 -> aad11209e


[SPARK-18633][ML][EXAMPLE] Add multiclass logistic regression summary python 
example and document

## What changes were proposed in this pull request?
Logistic Regression summary is added in Python API. We need to add example and 
document for summary.

The newly added example is consistent with Scala and Java examples.

## How was this patch tested?

Manually tests: Run the example with spark-submit; copy & paste code into 
pyspark; build document and check the document.

Author: wm...@hotmail.com <wm...@hotmail.com>

Closes #16064 from wangmiao1981/py.


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/aad11209
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/aad11209
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/aad11209

Branch: refs/heads/master
Commit: aad11209eb4db585f991ba09d08d90576f315bb4
Parents: bec0a92
Author: wm...@hotmail.com <wm...@hotmail.com>
Authored: Wed Dec 7 18:12:49 2016 -0800
Committer: Joseph K. Bradley <jos...@databricks.com>
Committed: Wed Dec 7 18:12:49 2016 -0800

----------------------------------------------------------------------
 docs/ml-classification-regression.md            | 10 ++-
 .../ml/logistic_regression_summary_example.py   | 68 ++++++++++++++++++++
 2 files changed, 76 insertions(+), 2 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/aad11209/docs/ml-classification-regression.md
----------------------------------------------------------------------
diff --git a/docs/ml-classification-regression.md 
b/docs/ml-classification-regression.md
index 5759593..bb9390f 100644
--- a/docs/ml-classification-regression.md
+++ b/docs/ml-classification-regression.md
@@ -114,9 +114,15 @@ Continuing the earlier example:
 {% include_example 
java/org/apache/spark/examples/ml/JavaLogisticRegressionSummaryExample.java %}
 </div>
 
-<!--- TODO: Add python model summaries once implemented -->
 <div data-lang="python" markdown="1">
-Logistic regression model summary is not yet supported in Python.
+[`LogisticRegressionTrainingSummary`](api/python/pyspark.ml.html#pyspark.ml.classification.LogisticRegressionSummary)
+provides a summary for a
+[`LogisticRegressionModel`](api/python/pyspark.ml.html#pyspark.ml.classification.LogisticRegressionModel).
+Currently, only binary classification is supported. Support for multiclass 
model summaries will be added in the future.
+
+Continuing the earlier example:
+
+{% include_example python/ml/logistic_regression_summary_example.py %}
 </div>
 
 </div>

http://git-wip-us.apache.org/repos/asf/spark/blob/aad11209/examples/src/main/python/ml/logistic_regression_summary_example.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/ml/logistic_regression_summary_example.py 
b/examples/src/main/python/ml/logistic_regression_summary_example.py
new file mode 100644
index 0000000..bd440a1
--- /dev/null
+++ b/examples/src/main/python/ml/logistic_regression_summary_example.py
@@ -0,0 +1,68 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+from __future__ import print_function
+
+# $example on$
+from pyspark.ml.classification import LogisticRegression
+# $example off$
+from pyspark.sql import SparkSession
+
+"""
+An example demonstrating Logistic Regression Summary.
+Run with:
+  bin/spark-submit 
examples/src/main/python/ml/logistic_regression_summary_example.py
+"""
+
+if __name__ == "__main__":
+    spark = SparkSession \
+        .builder \
+        .appName("LogisticRegressionSummary") \
+        .getOrCreate()
+
+    # Load training data
+    training = 
spark.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt")
+
+    lr = LogisticRegression(maxIter=10, regParam=0.3, elasticNetParam=0.8)
+
+    # Fit the model
+    lrModel = lr.fit(training)
+
+    # $example on$
+    # Extract the summary from the returned LogisticRegressionModel instance 
trained
+    # in the earlier example
+    trainingSummary = lrModel.summary
+
+    # Obtain the objective per iteration
+    objectiveHistory = trainingSummary.objectiveHistory
+    print("objectiveHistory:")
+    for objective in objectiveHistory:
+        print(objective)
+
+    # Obtain the receiver-operating characteristic as a dataframe and 
areaUnderROC.
+    trainingSummary.roc.show()
+    print("areaUnderROC: " + str(trainingSummary.areaUnderROC))
+
+    # Set the model threshold to maximize F-Measure
+    fMeasure = trainingSummary.fMeasureByThreshold
+    maxFMeasure = 
fMeasure.groupBy().max('F-Measure').select('max(F-Measure)').head()
+    bestThreshold = fMeasure.where(fMeasure['F-Measure'] == 
maxFMeasure['max(F-Measure)']) \
+        .select('threshold').head()['threshold']
+    lr.setThreshold(bestThreshold)
+    # $example off$
+
+    spark.stop()


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