Classification Based on the Optimal K-Associated Network
In this paper, we propose a new graph-based classifier which uses a special network, referred to as optimal K-associated network, for modeling data. The K-associated network is capable of representing (dis)similarity relationships among data samples and data classes. Here, we describe the main properties of the K-associated network as well as the classification algorithm based on it. Experimental evaluation indicates that the model based on an optimal K-associated network captures topological structure of the training data leading to good results on the classification task particularly for noisy data.
KeywordsComplex Network Data Mining Data Classification Network formation
Unable to display preview. Download preview PDF.
- 9.Berkhin, P.: Survey of Clustering Data Mining Techniques. Technical report, Accrue Software (2002)Google Scholar
- 12.Guha, S., Rastogi, R., Shim, K.: CURE: An Efficient Clustering Algorithm for Large Databases. In: Proc. of 1998 ACM-SIGMOD Int. Conf. on Management of Data, pp. 73–84 (1998)Google Scholar
- 13.Newman, M.E.J., Girvan, M.: Finding and Evaluating Community Structure in Networks. Physical Review E 69, 026113(1-15) (2004)Google Scholar
- 14.Danon, L., Duch, J., Arenas, A., Dáz-Guilera, A.: Comparing Community Structure Identification. Journal of Statistical Mechanics: Theory and Experiment, P09008(1-10) (2005)Google Scholar
- 17.Asuncion, A., Newman, D.J.: UCI Machine Learning Repository. University of California, School of Information and Computer Science, Irvine, CA (2007), http://www.ics.uci.edu/~mlearn/MLRepository.html