A new measure of groups perturbation

Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting, IFSA/NAFIPS 2013

Volumn , Issue , 2013, Pages 1291-1296

  Krawczak, M ^a   Szkatula, G ^a  

^a SYSTEMS RESEARCH INSTITUTE   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

APPLIED RESEARCH; CLUSTERING PROBLEMS; CONTINUOUS-VALUED ATTRIBUTE; HIGH SPEED; NON-EMPTY GROUPS;

EID: 84886535666     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IFSA-NAFIPS.2013.6608588     Document Type: Conference Paper

References (11)

1. Apostolico R., Bock M. E., Lonardi S. (2002). Monotony of surprise in large-scale quest for unusual words. In: Proceedings of the 6th International conference on research in computational molecular biology, Washington, DC, April 18-21, 22-31.
2. Gionis A., Mannila H. (2003). Finding recurrent sources in sequences. In: Proceedings of the 7th International conference on research in principles of database systems, Tucson, AZ, May 12-14, 249-256.
3. Johnson S. C. (1967). Hierarchical Clustering Schemes, Psychometrika, 2:241-254.
4. Krawczak M., Szkatuła G. (2010a). On time series envelopes for classification problem. In: Developments of fuzzy sets, intuitionistic fuzzy sets, generalized nets, vol. II, 2010.
5. Krawczak M., Szkatuła G. (2010b). Time series envelopes for classification. In: Proceedings of the conference: 2010 IEEE International Conference on Intelligent Systems, London, UK, July 7-9 2010, 156-161.
6. Krawczak M., Szkatuła G. (2011). A hybrid approach to dimension reduction in classification. Control and Cybernetics. 1, 2, 527-551.
7. Krawczak M., Szkatuła G. (2012a). A clustering algorithm based on distinguishability for nominal attributes. Lecture Notes in Artificial Intelligence, Vol. 7268, Springer-Verlag, 120-127.
8. Krawczak M., Szkatuła G. (2012b). Dimension reduction of time series for the Clustering Problem. W: Atanassov K., Homenda W., Hryniewicz O., Kacprzyk J., Krawczak M., Nahorski Z., Szmidt E., Zadrozny S. (Eds.): New Developments in Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets and Related Topics. Vol II: Applications. SRI PAS/IBS PAN, Warszawa 2012, 101-110.
9. Krawczak M., Szkatuła G. (2012c). Nominal Time Series Representation for the Clustering Problem, 2012 IEEE 6th International Conference "Intelligent Systems", Sofia, 182-187.
10. Lin, J., Keogh, E., Wei, L., Lonardi, S. (2007). Experiencing SAX: a Novel Symbolic Representation of Time Series. Data Min Knowledge Disc, 2, 15, 107-144.
11. Wang B. (2010). A New Clustering Algorithm on Nominal Data Sets. Proceedings of International Multi Conference of Engineers and Computer Scientists 2010 IMECS, 2010, March 17-19, Hong Kong.