Threshold tuning for improved classification association rule mining

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3518 LNAI, Issue , 2005, Pages 216-225

  Coenen, Frans ^a   Leng, Paul ^a   Zhang, Lu ^b  

^a UNIVERSITY OF LIVERPOOL   (United Kingdom)

^b PEKING UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); DATA REDUCTION;

ASSOCIATION RULE MINING (ARM); CLASSIFICATION ASSOCIATION RULES (CARS);

DATA MINING;

EID: 26944467164     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11430919_27     Document Type: Conference Paper

References (10)

1. Agrawal, R., Imielinski, T. and Swami, A.: Mining Association Rules between Sets of Items in Large Databases. Proc. ACM SIGMOD Conference on Management of Data, 207-216, 1993.
2. Agrawal, R. and Srikant, R.: Fast Algorithms for Mining Association Rules. Proc. of the 20th VLDB Conference, Santiago, Chile, 487-499, 1994.
3. Coenen, F., Goulbourne, G., and Leng, P.: Computing Association Rules using Partial Totals. PKDD 2001, pages 54-66, 2001.
4. Cohen, W.W.: Fast Effective Rule Induction. Proc. of the 12th Int. Conf. on Machine Learning, pages115-123, 1995.
5. Han, J., Pei, J. and Yin, Y.: Mining Frequent Patterns without Candidate Generation. In Proc. of the ACM SIGMOD Conference on Management of Data, Dallas, pages 1-12, 2000.
6. Liu, B., Hsu, W. and Ma, Y.: Integrating Classification and Association Rule Mining. Proc KDD 1998, 80-86
7. Li, W., Han, J. and Pei, J.: CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules. Proc ICDM'01, 2001, 369-376
8. Quinlan, J.R. C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993.
9. Quinlan, J.R. and Cameron-Jones, R.M.: FOIL: A midterm report. Proc ECML 1993, 3-20.
10. Yin, X. and Han, J.: CPAR: Classification Based on Predictive Association Rules. Proc SIAM Int Conf on Data Mining (SDM'03), 2003, 331-335