Mining MOUCLAS Patterns and Jumping MOUCLAS Patterns to Construct Classifiers - Data Mining: Theory, Methodology, Techniques, and Applications - page 129

3. B. Lent, A. Swami, and J. Widom. Clustering association rules. ICDE'97, (1997) 220-231
4. B. Liu, W.Hsu, and Y.Ma. Integrating classification and association rule mining. KDD'98.
(1998) 80-86
5. Meretakis, D., & Wuthrich, B. Extending naive Bayes classifiers using long itemsets. Proc.
of the Fifth ACM SIGKDD. ACM Press. (1999) 165-174
6. Jinyan Li, Guozhu Dong, Kotagiri Ramamohanarao. Making Use of the Most Expressive
Jumping Emerging Patterns for Classification. Knowledge and Information Systems,
3(2):131--145, 2001.
7. Quinlan, J. R. C4.5: Programs for machine learning. San Mateo, CA: Morgan Kaufmann.
(1993)
8. Cover, T. M., & Hart, P. E. Nearest neighbor pattern classification. IEEE Transactions on
Information Theory, 13. (1967) 21-27
9. R. Skikant and R. Agrawal. Mining quantitative association rules in large relational tables.
SIG-MOD'96, (1996) 1-12.
10. Fayyad, U., & Irani, K. Multi-interval discretization of continuous-valued attributes for
classification learning. Proc. of the 13th Int'l Conf. on Artificial Intelligence. Morgan
Kaufmann. (1993) 1022--1029
11. Dougherty, J., Kohavi, R., & Sahami, M. Supervised and unsupervised discretization of
continuous features. Proc. of the Twelfth Int'l Conf. on Machine Learning pp. 94--202.
Morgan Kaufmann. (1995)
12. Khalil M. Ahmed, Nagwa M. El-Makky, Yousry Taha: A note on "Beyond Market
Baskets: Generalizing Association Rules to Correlations". In The Proceedings of SIGKDD
Explorations Volume1, Issue 2, (2000) 46-48
13. Agrawal, R., Srikant, R. Fast algorithms for mining association rules. Proc. of the 20th
VLDB (1994) 487- 499
14. Bing Liu, Wynne Hsu, Yiming Ma, "Mining Association Rules with Multiple Minimum
Supports" Proceedings of the ACM SIGKDD International Conference on Knowledge
Discovery & Data Mining (KDD-99), August 15-18, San Diego, CA, USA (1999)
15. Dong, G., & Li, J. Feature selection methods for classification. Intelligent Data Analysis:
An International Journal, 1, (1997)
16. H. Liu and H. Motoda, editors. Feature Selection for Knowledge Discovery and Data
Mining. Boston: Kluwer Academic Publishers, (1998)
17. W.Sarawagi and M. Stonebraker. On automatic feature selection. Int'l J. of Pattern
Recognition and Artificial Intelligence, 2, (1988) 197-220.
18. R. Kohavi and G. John. Wrappers for feature subset selection. Artificial Intelligence,
(1997) 273-324
19. Yager, R. and D. Filev, "Generation of Fuzzy Rules by Mountain Clustering," Journal of
Intelligent & Fuzzy Systems, Vol. 2, No. 3, (1994) 209-219
20. Chiu, S. L. Fuzzy model identification based on cluster estimation. Journal of Intelligent
and Fuzzy System, 2(3), (1994)
21. A. Hinneburg and D. Keim. An efficient approach to clustering in large Multimedia
dataset with noise. KDD'98, (1998) 58-65
22. R. Agrawal, J. Gehrke, D. Gunopulos, and P. Raghavan. Automatic subspace clustering of
high dimensional data for data mining applications. SIGMOD'98. (1998)