Handling big data with fuzzy based classification approach

Studies in Fuzziness and Soft Computing

Volumn 312, Issue , 2014, Pages 219-227

  Bharill, Neha ^a   Tiwari, Aruna ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY INDORE   (India)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84958532873     PISSN: 14349922     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-319-03674-8_21     Document Type: Conference Paper

References (8)

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2. Cai, W., Chen, S., Zhang, D.: A Multiobjective Simultaneous Learning Framework for Clustering and Classification. IEEE Trans. on Neural Networks 21(2), 185-200 (2010)
3. Kaufman, L., Rousseeuw, P.: Finding Groups in Data: An Introduction to Cluster Analysis. Wiley-Blackwell, New Work (2005)
4. Guha, L.S., Rastogi, R., Shim, K.: CURE: An efficient clustering algorithm for large databases. Inf. Syst. 26(1), 35-58 (2001)
5. Har-Peled, S., Mazumdar, S.: On coresets for k-means and k-median clustering. In: Proc. ACM Symp. Theory Comput., pp. 291-300 (2004)
6. Shankar, B.U., Pal, N.: FFCM: An efficient approach for large data sets. In: Proc. Int. Conf. Fuzzy Logic, Neural Nets, Soft Comput., Fukuoka, Japan, p. 332 (1994)
7. Cheng, T., Goldgof, D., Hall, L.: Fast clustering with application to fuzzy rule generation. In: Proc. Int. Conf. Fuzzy Syst., Tokyo, Japan, pp. 2289-2295 (1995)
8. Blake, C., Keogh, E., Merz, C.J.: UCI Repository of Machine learning Databases. Dept. Inf. Comput. Sci., Univ. California Irvine, Irvine (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html