'Incrementally fit the model to data.
Fit a separate model for each output variable.
Parameters
X : (sparse) array-like, shape (n_samples, n_features)
Data.
y : (sparse) array-like, shape (n_samples, n_outputs)
Multi-output targets.
sample_weight : array-like, shape = (n_samples) or None
Sample weights. If None, then samples are equally weighted.
Only supported if the underlying regressor supports sample
weights.
Returns
self : object
Returns self.'

@if_delegate_has_method('estimator')
def partial_fit(self, X, y, sample_weight=None):

    super(MultiOutputRegressor, self).partial_fit(X, y, sample_weight=sample_weight)
