def train(self, input_train, epsilon=1e-5, epochs=100):
        n_clusters = self.n_clusters
        input_train = format_data(input_train)

        if input_train.shape[0] <= n_clusters:
            raise ValueError("Count of clusters must be less than count of "
                             "input data.")

        self.centers = input_train[:n_clusters, :].copy()
        super(RBFKMeans, self).train(input_train, epsilon=epsilon,
                                     epochs=epochs)
dataset/ETHPy150Open itdxer/neupy/neupy/algorithms/rbfn/rbf_kmeans.py/RBFKMeans.train/original