[SPARK-7648] [MLLIB] Add weights and intercept to GLM wrappers in spark.ml

Otherwise, users can only use `transform` on the models. brkyvz

Author: Xiangrui Meng <meng@databricks.com>

Closes #6156 from mengxr/SPARK-7647 and squashes the following commits:

1ae3d2d [Xiangrui Meng] add weights and intercept to LogisticRegression in Python
f49eb46 [Xiangrui Meng] add weights and intercept to LinearRegressionModel

1 files changed, 7 insertions, 1 deletions

diff --git a/python/pyspark/ml/wrapper.py b/python/pyspark/ml/wrapper.py
index f5ac2a3986..dda6c6aba3 100644
--- a/python/pyspark/ml/wrapper.py
+++ b/python/pyspark/ml/wrapper.py
@@ -21,7 +21,7 @@ from pyspark import SparkContext
 from pyspark.sql import DataFrame
 from pyspark.ml.param import Params
 from pyspark.ml.pipeline import Estimator, Transformer, Evaluator, Model
-from pyspark.mllib.common import inherit_doc
+from pyspark.mllib.common import inherit_doc, _java2py, _py2java
 
 
 def _jvm():
@@ -149,6 +149,12 @@ class JavaModel(Model, JavaTransformer):
     def _java_obj(self):
         return self._java_model
 
+    def _call_java(self, name, *args):
+        m = getattr(self._java_model, name)
+        sc = SparkContext._active_spark_context
+        java_args = [_py2java(sc, arg) for arg in args]
+        return _java2py(sc, m(*java_args))
+
 
 @inherit_doc
 class JavaEvaluator(Evaluator, JavaWrapper):