splearn/linear_model/stochastic_gradient.py
def fit(self, Z, classes=None):
        """Fit the model according to the given training data.

        Parameters
        ----------
        Z : DictRDD containing (X, y) pairs
            X - Training vector
            y - Target labels
        classes : iterable
            The set of available classes

        Returns
        -------
        self : object
            Returns self.
        """
        check_rdd(Z, {'X': (sp.spmatrix, np.ndarray)})
        self._classes_ = np.unique(classes)
        return self._spark_fit(SparkSGDClassifier, Z)
def fit(self, Z, classes=None):
        """Fit the model according to the given training data.

        Parameters
        ----------
        Z : DictRDD containing (X, y) pairs
            X - Training vector
            y - Target labels
        classes : iterable
            The set of available classes

        Returns
        -------
        self : object
            Returns self.
        """
        check_rdd(Z, {'X': (sp.spmatrix, np.ndarray)})
        self._classes_ = np.unique(classes)
        return self._spark_fit(SparkSGDClassifier, Z)
Fit the model according to the given training data.

        Parameters
        ----------
        Z : DictRDD containing (X, y) pairs
            X - Training vector
            y - Target labels
        classes : iterable
            The set of available classes

        Returns
        -------
        self : object
            Returns self.