Github user MLnick commented on a diff in the pull request:

    https://github.com/apache/spark/pull/11183#discussion_r54251532
  
    --- Diff: python/pyspark/mllib/classification.py ---
    @@ -272,37 +275,42 @@ def train(cls, data, iterations=100, step=1.0, 
miniBatchFraction=1.0,
             """
             Train a logistic regression model 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 miniBatchFraction: Fraction of data to be used for each
    -                                  SGD iteration (default: 1.0).
    -        :param initialWeights:    The initial weights (default: None).
    -        :param regParam:          The regularizer parameter
    -                                  (default: 0.01).
    -        :param regType:           The type of regularizer used for
    -                                  training our model.
    -
    -                                  :Allowed values:
    -                                     - "l1" for using L1 regularization
    -                                     - "l2" for using L2 regularization
    -                                     - None for no regularization
    -
    -                                     (default: "l2")
    -
    -        :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,
    -                                  default: False).
    -        :param validateData:      Boolean parameter which indicates if
    -                                  the algorithm should validate data
    -                                  before training. (default: True)
    -        :param convergenceTol:    A condition which decides iteration 
termination.
    -                                  (default: 0.001)
    +        :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 miniBatchFraction:
    +          Fraction of data to be used for each SGD iteration.
    +          (default: 1.0)
    +        :param initialWeights:
    +          The initial weights.
    +          (default: None)
    +        :param regParam:
    +          The regularizer parameter.
    +          (default: 0.01)
    +        :param regType:
    +          The type of regularizer used for training our model.
    +          Allowed values:
    +
    +            - "l1" for using L1 regularization
    +            - "l2" for using L2 regularization (default)
    +            - None for no regularization
    --- End diff --
    
    Are we going to move the default to the line below: `(default: "l2")`?


---
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 [email protected] or file a JIRA ticket
with INFRA.
---

---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]

Reply via email to