References
- A.K. Jain, "Data Clustering: 50 Years Beyond K-means," Pattern Recognition Lett., vol. 31, no. 8, June 2010, pp. 651-666. https://doi.org/10.1016/j.patrec.2009.09.011
- J. Han and M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, 2nd ed., 2007.
- J. Mao and A.K. Jain, "A Self-Organizing Network for Hyperellipsoidal Clustering (HEC)," IEEE Trans. Neural Netw., vol. 7, no. 1, Jan. 1996, pp. 16-29. https://doi.org/10.1109/72.478389
- W. Song et al., "The Hyperellipsoidal Clustering Using Genetic Algorithm," IEEE Int. Conf. Intell. Process. Syst., Beijing, China, Oct. 28-31, 1997, pp. 592-596.
- H. Ichihashi, M. Ohue, and T. Miyoshi, "Fuzzy C-Means Clustering Algorithm with Pseudo Mahalanobis Distances," Proc. Third Asian Fuzzy Syst. Symp., Changwon, Rep. of Korea, June 18-21, 1998, pp. 148-152.
- M. Moshtaghi et al., "An Efficient Hyperellipsoidal Clustering Algorithm for Resource-Constrained Environments," Pattern Recogn., vol. 44, no. 9, Sept. 2011, pp. 2197-2209. https://doi.org/10.1016/j.patcog.2011.03.007
- W. Song et al., "Comments on a Self-Organizing Network for Hyper-ellipsoidal Clustering (HEC)," IEEE Trans. Neural Netw., vol. 8, no. 6, Nov. 1997, pp. 1561-1563. https://doi.org/10.1109/72.641479
- R. Krishnapuram and J. Kim, "A Clustering Algorithm Based on Minimum Volume," IEEE Int. Conf. Fuzzy Syst., vol. 2, New Orleans, LA, USA, Sept. 8-11, 1996, pp. 1387-1392.
- H. Lee, J. Park, and D. Park, "Hyper-ellipsoidal Clustering Algorithm Using Linear Matrix Inequality," J. Korea Institute Intell. Syst., vol. 12, no. 4, Aug. 2002, pp. 300-305. https://doi.org/10.5391/JKIIS.2002.12.4.300
- M. Kumar and J.B. Orlin, "Scale-Invariant Clustering with Minimum Volume Ellipsoids," Comput. Operations. Res., vol. 35, no. 4, Apr. 2008, pp. 1017-1029. https://doi.org/10.1016/j.cor.2006.07.001
- R. Shioda and L. Tuncel, "Clustering via Minimum Volume Ellipsoids," Comput. Optim. Appl., vol. 37, no. 3, July 2007, pp. 247-295. https://doi.org/10.1007/s10589-007-9024-1
- S. Boyd and L. Vandenberghe, Convex Optimization, 1st ed., Cambridge, UK: Cambridge University Press, 2004.
- M.J. Todd and E.A. Yildirim, "On Khachiyan's Algorithm for the Computation of Minimum-Volume Enclosing Ellipsoids," Discr. Appl. Math., vol. 155, no. 13, Aug. 15, 2007, pp. 1731-1744. https://doi.org/10.1016/j.dam.2007.02.013
- N. Moshtagh, Minimum Volume Enclosing Ellipsoids, Tech. report, the School of Engineering and Applied Science, Univ. Pennsylvania, PA, 2005.
- P. Kumar and E.A. Yildirim, "Minimum Volume Enclosing Ellipsoids and Core Set," J. Optim. Theory Appl., vol. 126, no. 1, July 2005, pp. 1-21. https://doi.org/10.1007/s10957-005-2653-6
- J. Cao et al., "A Max-Flow-Based Similarity Measure for Spectral Clustering," ETRI J., vol. 35, no. 2, Apr. 2013, pp. 311-320. https://doi.org/10.4218/etrij.13.0112.0520
- J. Shawe-Taylor and N. Cristianini, Kernel Methods for Pattern Analysis, Cambridge, UK: Cambridge University Press, 2004.
- B. Scholkopf, A. Smola, and K.-R. Muller, "Kernel Principal Component Analysis," Proc. ICANN, LNCS, Lausanne, Switzerland, vol. 1327, Oct. 8-10, 1997, pp. 583-588.
- D. Tax and P. Juszczak, "Kernel Whitening for One-Class Classification," Proc. Pattern Recogn. Support Vector Mach., Niagara Fall, Canada, vol. 2388, Aug. 10, 2002, pp. 40-52.
- CVX Research, Inc. CVX: Matlab Software for Disciplined Convex Programming, version 2.0. Accessed Apr. 2013. http://cvxr.com/cvx
- M. Grant and S. Boyd, "Graph Implementations for Nonsmooth Convex Programs," Recent Advances Learning Contr. LNCIS, vol. 371, 2008, pp. 95-110.
- D. Cai, X. He, and J. Han, "Document Clustering Using Locality Preserving Indexing," IEEE Trans. KDE, vol. 17, no. 12, Dec. 2005, pp. 1624-1637.
- The machine learning dataset of UCI are available. Accessed Jan. 2013. http://archive.ics.uci.edu/ml/
Cited by
- Wind Power Pattern Forecasting Based on Projected Clustering and Classification Methods vol.37, pp.2, 2014, https://doi.org/10.4218/etrij.15.2314.0070
- Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps vol.37, pp.6, 2014, https://doi.org/10.4218/etrij.15.0114.0112
- Affine-transformation invariant clustering models vol.7, pp.None, 2014, https://doi.org/10.1186/s40488-020-00111-y