viirya commented on a change in pull request #30413:
URL: https://github.com/apache/spark/pull/30413#discussion_r529113536
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File path: python/pyspark/mllib/classification.py
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@@ -501,53 +525,59 @@ def load(cls, sc, path):
class SVMWithSGD(object):
"""
+ Train a Support Vector Machine (SVM) using Stochastic Gradient Descent.
+
.. versionadded:: 0.9.0
"""
@classmethod
- @since('0.9.0')
def train(cls, data, iterations=100, step=1.0, regParam=0.01,
miniBatchFraction=1.0, initialWeights=None, regType="l2",
intercept=False, validateData=True, convergenceTol=0.001):
"""
Train a support vector machine on the given data.
- :param data:
- The training data, an RDD of LabeledPoint.
- :param iterations:
- The number of iterations.
- (default: 100)
- :param step:
- The step parameter used in SGD.
- (default: 1.0)
- :param regParam:
- The regularizer parameter.
- (default: 0.01)
- :param miniBatchFraction:
- Fraction of data to be used for each SGD iteration.
- (default: 1.0)
- :param initialWeights:
- The initial weights.
- (default: None)
- :param regType:
- The type of regularizer used for training our model.
- Allowed values:
+ .. versionadded:: 0.9.0
+
+ Parameters
+ ----------
+ data : :py:class:`pyspark.RDD`
+ The training data, an RDD of
:py:class:`pyspark.mllib.regression.LabeledPoint`.
+ iterations : int, optional
+ The number of iterations.
+ (default: 100)
+ step : float, optional
+ The step parameter used in SGD.
+ (default: 1.0)
+ regParam : float, optional
+ The regularizer parameter.
+ (default: 0.01)
+ miniBatchFraction: float, optional
Review comment:
miniBatchFraction: -> miniBatchFraction :
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