#NEWLINE# def predict( self , X ) : #NEWLINE# #INDENT# 'Predict class labels of X.\n\n        Parameters\n        ----------\n        X : {array-like, sparse matrix}, shape = [n_samples, n_features]\n            Training vectors, where n_samples is the number of samples and\n            n_features is the number of features.\n\n        Returns\n        ----------\n        class_labels : array-like, shape = [n_samples]\n            Predicted class labels.\n\n        ' #NEWLINE# self . _check_arrays ( X ) #NEWLINE# if ( not self . _is_fitted ) : #NEWLINE# #INDENT# raise AttributeError ( 'Model is not fitted, yet.' ) #NEWLINE# #UNINDENT# return self . _predict ( X ) . flatten ( )