1. M. Kubat, S. Matwin, Addressing the curse of imbalanced training sets: one-sided selection, Proceedings of the 14th International Conference on Machine Learning, Nashville, USA, 1997, pp. 179–186.
2. T. Eavis, N. Japkowicz, A recognition-based Alternative to Discrimination-based Multi-layer Perceptrons, Advances in Artificial Intelligence, Lecture Notes in Computer Science, Vol. 1822, Springer, Berlin, 2000, pp. 280–292.
3. Asymptotic properties of nearest neighbor rules using edited data sets;Wilson;IEEE Trans. Systems Man Cybern.,1972
4. F.J. Ferri, J.S. Sánchez, F. Pla, Editing Prototypes in the Finite Sample Size Case Using Alternative Neighbourhoods, Advances in Pattern Recognition, Lecture Notes in Computer Science, Vol. 1451, Springer, Berlin, 1998, pp. 620–629.
5. R. Barandela, N. Cortés, A. Palacios, The nearest neighbor rule and the reduction of the training sample size, Proceedings of the Ninth Spanish Symposium on Pattern Recognition and Image Analysis 1, Benicàssim, Spain, 2001, pp. 103–108.