def partial_fit(self, X, y):
X, y = filter_by_label(X, y, self.reference_label)<EOL>super().partial_fit(X, y)<EOL>return self<EOL>
:X: {array-like, sparse matrix}, shape [n_samples, n_features]
    The data used to compute the mean and standard deviation
    used for later scaling along the features axis.
:y: Healthy 'h' or 'sick_name'