Class LogisticRegressionWithSGD

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).