def predict(self, input_data):
        input_data = format_data(input_data)

        centers = self.centers
        classes = zeros((input_data.shape[0], 1))

        for i, value in enumerate(input_data):
            classes[i] = argmin(norm(centers - value, axis=1))

        return classes
dataset/ETHPy150Open itdxer/neupy/neupy/algorithms/rbfn/rbf_kmeans.py/RBFKMeans.predict/original