python/pyspark/mllib/classification.py
def train(cls, data, iterations=100, step=1.0,
              miniBatchFraction=1.0, initialWeights=None):
        """Train a logistic regression model on the given data."""
        sc = data.context
        return _regression_train_wrapper(sc, lambda d, i:
                sc._jvm.PythonMLLibAPI().trainLogisticRegressionModelWithSGD(d._jrdd,
                        iterations, step, miniBatchFraction, i),
                LogisticRegressionModel, data, initialWeights)
Train a logistic regression model on the given data.
Train a logistic regression model on the given data.
Train a logistic regression model on the given data .
def train(cls, data, iterations=100, step=1.0,
              miniBatchFraction=1.0, initialWeights=None):
        sc = data.context
        return _regression_train_wrapper(sc, lambda d, i:
                sc._jvm.PythonMLLibAPI().trainLogisticRegressionModelWithSGD(d._jrdd,
                        iterations, step, miniBatchFraction, i),
                LogisticRegressionModel, data, initialWeights)
def train ( cls , data , iterations = 100 , step = 1.0 , miniBatchFraction = 1.0 , initialWeights = None ) : sc = data . context return _regression_train_wrapper ( sc , lambda d , i : sc . _jvm . PythonMLLibAPI ( ) . trainLogisticRegressionModelWithSGD ( d . _jrdd , iterations , step , miniBatchFraction , i ) , LogisticRegressionModel , data , initialWeights )
Train a logistic regression model on the given data.
Train a logistic regression model on the given data .
"""Train a logistic regression model on the given data."""
cls
data
iterations
step
miniBatchFraction
initialWeights