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-rw-r--r--python/pyspark/mllib/regression.py15
1 files changed, 9 insertions, 6 deletions
diff --git a/python/pyspark/mllib/regression.py b/python/pyspark/mllib/regression.py
index 8fe8c6db2a..54f34a9833 100644
--- a/python/pyspark/mllib/regression.py
+++ b/python/pyspark/mllib/regression.py
@@ -22,7 +22,7 @@ from pyspark import SparkContext
from pyspark.mllib.linalg import SparseVector, _convert_to_vector
from pyspark.serializers import PickleSerializer, AutoBatchedSerializer
-__all__ = ['LabeledPoint', 'LinearModel', 'LinearRegressionModel', 'RidgeRegressionModel'
+__all__ = ['LabeledPoint', 'LinearModel', 'LinearRegressionModel', 'RidgeRegressionModel',
'LinearRegressionWithSGD', 'LassoWithSGD', 'RidgeRegressionWithSGD']
@@ -155,11 +155,14 @@ class LinearRegressionWithSGD(object):
@param regParam: The regularizer parameter (default: 1.0).
@param regType: The type of regularizer used for training
our model.
- Allowed values: "l1" for using L1Updater,
- "l2" for using
- SquaredL2Updater,
- "none" for no regularizer.
- (default: "none")
+
+ :Allowed values:
+ - "l1" for using L1Updater,
+ - "l2" for using SquaredL2Updater,
+ - "none" for no regularizer.
+
+ (default: "none")
+
@param intercept: Boolean parameter which indicates the use
or not of the augmented representation for
training data (i.e. whether bias features