spark-reviews mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From miccagiann <>
Subject [GitHub] spark pull request: [SPARK-2550][MLLIB][APACHE SPARK] Support regu...
Date Tue, 05 Aug 2014 07:19:23 GMT
Github user miccagiann commented on a diff in the pull request:
    --- Diff: python/pyspark/mllib/ ---
    @@ -73,11 +73,36 @@ def predict(self, x):
     class LogisticRegressionWithSGD(object):
    -    def train(cls, data, iterations=100, step=1.0, miniBatchFraction=1.0, initialWeights=None):
    -        """Train a logistic regression model on the given data."""
    +    def train(cls, data, iterations=100, step=1.0, miniBatchFraction=1.0,
    +              initialWeights=None, regParam=1.0, regType=None, intercept=False):
    +        """
    +        Train a logistic regression model on the given data.
    +        @param data:              The training data.
    +        @param iterations:        The number of iterations (default: 100).
    +        @param step:              The step parameter used in SGD
    +                                  (default: 1.0).
    +        @param miniBatchFraction: Fraction of data to be used for each SGD
    +                                  iteration.
    +        @param initialWeights:    The initial weights (default: None).
    +        @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")
    +        @param intercept:         Boolean parameter which indicates the use
    +                                  or not of the augmented representation for
    +                                  training data (i.e. whether bias features
    +                                  are activated or not).
    +        """
             sc = data.context
    +        if regType is None:
    --- End diff --
    Ok! I will update the code with the suggested approach of MLnick...

If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at or file a JIRA ticket
with INFRA.

To unsubscribe, e-mail:
For additional commands, e-mail:

View raw message