Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/4151#discussion_r23657099
--- Diff: python/pyspark/ml/classification.py ---
@@ -0,0 +1,88 @@
+#
+# 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 pyspark.sql import inherit_doc
+from pyspark.ml import JavaEstimator, JavaModel
+from pyspark.ml.param.shared import HasFeaturesCol, HasLabelCol,
HasPredictionCol, HasMaxIter,\
+ HasRegParam
+
+
+@inherit_doc
+class LogisticRegression(JavaEstimator, HasFeaturesCol, HasLabelCol,
HasPredictionCol, HasMaxIter,
+ HasRegParam):
+ """
+ Logistic regression.
+
+ >>> from pyspark.sql import Row
+ >>> from pyspark.mllib.linalg import Vectors
+ >>> dataset = sqlCtx.inferSchema(sc.parallelize([ \
+ Row(label=1.0, features=Vectors.dense(1.0)), \
+ Row(label=0.0, features=Vectors.sparse(1, [], []))]))
+ >>> lr = LogisticRegression() \
+ .setMaxIter(5) \
+ .setRegParam(0.01)
+ >>> model = lr.fit(dataset)
+ >>> test0 =
sqlCtx.inferSchema(sc.parallelize([Row(features=Vectors.dense(-1.0))]))
+ >>> print model.transform(test0).first().prediction
+ 0.0
+ >>> test1 =
sqlCtx.inferSchema(sc.parallelize([Row(features=Vectors.sparse(1, [0],
[1.0]))]))
+ >>> print model.transform(test1).first().prediction
+ 1.0
+ """
+
+ def __init__(self):
+ super(LogisticRegression, self).__init__()
+
+ @property
+ def _java_class(self):
+ return "org.apache.spark.ml.classification.LogisticRegression"
+
+ def _create_model(self, java_model):
+ return LogisticRegressionModel(java_model)
+
+
+@inherit_doc
+class LogisticRegressionModel(JavaModel):
+ """
+ Model fitted by LogisticRegression.
+ """
+
+ def __init__(self, java_model):
+ super(LogisticRegressionModel, self).__init__()
+ self._java_model = java_model
--- End diff --
I'd like to move this into JavaModel
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