SACOC:A Spectral-Based ACO Clustering Algorithm
The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach.Most recent works concerning unsupervised learning have been focused on clustering, where ACO-based techniques have showed a great potential. At the same time, new clustering techniques that seek the continuity of data, specially focused on spectral-based approaches in opposition to classical centroid-based approaches, have attracted an increasing research interest—an area still under study by ACO clustering techniques. This work presents a hybrid spectral-based ACO clustering algorithm inspired by the ACO Clustering (ACOC) algorithm. The proposed approach combines ACOC with the spectral Laplacian to generate a new search space for the algorithm in order to obtain more promising solutions. The new algorithm, called SACOC, has been compared against well-known algorithms (K-means and Spectral Clustering) and with ACOC. The experimentsmeasure the accuracy of the algorithm for both synthetic datasets and realworld datasets extracted from the UCI Machine Learning Repository.
KeywordsClustering Data Mining ACO Spectral
Unable to display preview. Download preview PDF.
- 1.Ashok, L., Messinger, D.W.: A spectral image clustering algorithm based on ant colony optimization, pp. 83,901P–83,901P–10 (2012)Google Scholar
- 2.Bache, K., Lichman, M.: UCI machine learning repository (2013), http://archive.ics.uci.edu/ml
- 7.Larose, D.T.: Discovering Knowledge in Data. John Wiley & Sons (2005)Google Scholar
- 9.Macqueen, J.B.: Some methods of classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, pp. 281–297 (1967)Google Scholar
- 11.Menéndez, H.D., Barrero, D.F., Camacho, D.: A genetic graph-based approach for partitional clustering. Int. J. Neural Syst. 24(3) (2014)Google Scholar
- 12.Ng, A., Jordan, M., Weiss, Y.: On Spectral Clustering: Analysis and an algorithm. In: Dietterich, T., Becker, S., Ghahramani, Z. (eds.) Advances in Neural Information Processing Systems, pp. 849–856. MIT Press (2001)Google Scholar
- 13.Orgaz, G.B., Menéndez, H.D., Camacho, D.: Adaptive k-means algorithm for overlapped graph clustering. Int. J. Neural Syst. 22(5) (2012)Google Scholar