Hybrid learning scheme for Data Mining applications

Proceedings - HIS'04: 4th International Conference on Hybrid Intelligent Systems

Volumn , Issue , 2005, Pages 266-271

  Babu, T Ravindra ^a   Murty, M Narasimha ^b   Agrawal, V K ^a,b  

^a INDIAN INSTITUTE OF SCIENCE   (India)

^b INDIAN SPACE RESEARCH ORGANISATION   (India)

Author keywords

[No Author keywords available]

Indexed keywords

HYBRID LEARNING APPROACH; ITEM GENERATION; LARGE DATASETS; ROUGH SETS;

ABSTRACTING; CLASSIFICATION (OF INFORMATION); DATA COMPRESSION; HYBRID COMPUTERS; SET THEORY;

DATA MINING;

EID: 28344435910     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In Proc. 1993 ACM-SIGMOD Int. Conf. Management of Data(SIGMOD'93), pages 207-216, 1993.
2. V. Ananthanarayana and M. N. Murty. Tree structure for efficient data mining using rough sets. Pattern Recognition Letters, 24(6):851-862, March 2003.
3. T. R. Babu and M. N. Murty. Comparison of genetic algorithm based prototype selection schemes. Pattern Recognition, 34(3):523-525, March 2001.
4. J. Deogun, V. Raghavan, and H. Sever. Rough set based classification methods for extended decision tables. In Proceedings of International Workshop on Rough Sets and Soft Computing, pages 302-309, 1994.
5. J. Han, J. Pei, and Y. Yin. Mining frequent patterns without candidate generation. In Proc. 2000 ACM-SIGMOD Int. Conf. Management of Data(SIGMOD'00), pages 1-12, 2000.
6. A. Jain and R. Dubes. Algorithm for clustering data. Prentice Hall, New Jersey, 1988.
7. D. Lelewer and D. Hirshberg. Data compression. ACM Computing Surveys, (9):261-296, September 1987.
8. Z. Pawlak, J. Grzymala-Busse, R. Slowinski, and W. Ziarko. Rough sets. Communications of the ACM, 38(11):89-95, November 1995.
9. K. Sayood. Introduction to Data Compression. Morgan Kaufmann Publishers, New Jersey, 2000.