Mining insightful classification rules directly and efficiently

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

Volumn 3, Issue , 1999, Pages

  Liu, Hongyan ^a   Chen, Jian ^a   Chen, Guoqing ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULES; CLASSIFICATION RULES;

ALGORITHMS; ASSOCIATIVE PROCESSING; CLASSIFICATION (OF INFORMATION); COMPUTATION THEORY; DATA STORAGE EQUIPMENT; DATABASE SYSTEMS; LOGIC PROGRAMMING;

DATA MINING;

EID: 0033339720     PISSN: 08843627     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. G. Piatetsky-Shapiro, U. Fayyad, P. Smyth, From data mining to knowledge discovery: An overview. Advances in Knowledge Discovery and Data Mining, AAAI/MIT press, 1996,pp.1∼35.
2. J. R. Quinlan, C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993.
3. Manish Mehta, Rakesh Agrawal and Jorma Rissanen, SLIQ: A Fast Scalable Classifier for Data Mining, Extending database technology, 1996, pp. 18-32.
4. J. Catlett. Megainduction: Machine Learning on Very Large Databases. PhD thesis, University of Sydney, 1991.
5. K. Alsabli, S. Ranka, V. Singh, CLOUDS: A decision Tree classifier for Large Data sets. In Proc. Of the Fourth hit. Conference on Knowledge Discovery & Data Mining. New York, New York, August 27-31, 1998, 2-8.
6. Bing Liu, Wynne Hsu and Yiming Ma. Integrity Classification and Association Rule Mining, In Proc. Of the Fourth Int. Conference on Knowledge Discovery & Data Mining. New York, New York, August 27-31, 1998, page 8086.
7. R. Agrawal, T. Imielinski, and A. Swami, Mining association rides between sets of items in laige databases. In: Proceeding of 1993 ACM-SIGMOD hit. Conf. On Management of Data, Washington, D.C., 1993, pp. 207-216.
8. R. Agrawal, R. Srikant. Fast algorithm for mining association rules. In Proc. Of the 20th VLDB Conference, Santiago, Chile, 1994, pp. 487-499.
9. J. S. Park, M. S, Chen, and P.S. Yu. An Effective Hash-based Algorithm for Mining Association rules. In: Proceedings of ACM-SIGMOD Int. Conf. On Management of Data, Baltimore, MD, 1995, pp. 175-186.
10. H. Toivonen, Sampling Large Databases for Association Rules, hi 22th International Conference on VLDB, Bombay, India. September 1996, pp. 134-145.
11. U.S. Brin, R. Motwani, J. Ullman, et al. Dynamic itemset counting and implication núes for market basket data. In Proc. Of 1997 ACM-SIGMOD Int. Conf. On Management of Data, Tucson, Arizona, 1997, pp. 255-264.
12. S. M. Weiss and C. A. Kulikowski. Computer Systems that Leant: Classification and prediction Methods from Statistics, Neural Nets, Machine Learning, and Expert Systems. Morgan Kaufman, 1991.
13. L. Breiman et. al. Classification and Regression Trees. Wadsworth, Belmont, 1984.
14. Rakesh Agrawal, Tomasz Imielinski, Arun Swami, Database Mining: A Performance Perspective, IEEE transaction on knowledge and data engineering, December 1993, 5(6), pp. 914-925.