def partial_fit(self, X, y, classes=None, sample_weight=None):
        if self.class_weight in ['balanced', 'auto']:
            raise ValueError("class_weight '{0}' is not supported for "
                             "partial_fit. In order to use 'balanced' weights,"
                             " use compute_class_weight('{0}', classes, y). "
                             "In place of y you can us a large enough sample "
                             "of the full training set target to properly "
                             "estimate the class frequency distributions. "
                             "Pass the resulting weights as the class_weight "
                             "parameter.".format(self.class_weight))
        return self._partial_fit(X, y, alpha=self.alpha, C=1.0, loss=self.loss,
                                 learning_rate=self.learning_rate, n_iter=1,
                                 classes=classes, sample_weight=sample_weight,
                                 coef_init=None, intercept_init=None)
Fit linear model with Stochastic Gradient Descent.
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/linear_model/stochastic_gradient.py/BaseSGDClassifier.partial_fit