Abstract
The KNN rule has been widely used in many pattern recognition problems, but it is sensible to noisy data within the training set, therefore, several sample edition methods have been developed in order to solve this problem. A. Franco, D. Maltoni and L. Nanni proposed the Reward-Punishment Editing method in 2004 for editing numerical databases, but it has the problem that the selected prototypes could belong neither to the sample nor to the universe. In this work, we propose a modification based on selecting the prototypes from the training set. To do this selection, we propose the use of the Fuzzy C-means algorithm for mixed data and the KNN rule with similarity functions. Tests with different databases were made and the results were compared against the original Reward-Punishment Editing and the whole set (without any edition).
This work was financially supported by CONACyT (Mexico) through the project J38707-A.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Wilson, D.R., Martínez, T.R.: Reduction Techniques for Instance-Based Learning Algorithms. Machine Learning 38, 257–286 (2000)
Paredes, R., Wagner, T.: Weighting prototypes, a new approach. In: The proceedings of International Conference on Pattern Recognition (ICPR), vol. II, pp. 25–28 (2000)
Franco, A., Maltoni, D., Nanni, L.: Reward- Punishment Editing. In: The proceedings of International Conference on Pattern Recognition, ICPR (2004) (In CD)
Ayaquica-Martínez, I.O., Martínez-Trinidad, J.F.: Fuzzy C-means algorithm to analyze mixed data. In: The proceedings of the 6th Iberoamerican Symposium on Pattern Recognition, Florianópolis, Brazil, pp. 27–33 (2001)
Blake, C.L., Merz, C.J.: UCI Repository of machine learning databases. Irvine, CA: University of California, Department of Information and Computer Science (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rodríguez-Colín, R., Carrasco-Ochoa, J.A., Martínez-Trinidad, J.F. (2005). Reward-Punishment Editing for Mixed Data. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_50
Download citation
DOI: https://doi.org/10.1007/11578079_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
eBook Packages: Computer ScienceComputer Science (R0)