Classification
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#1. C4.5
Quinlan, J. R. 1993. C4.5: Programs for Machine Learning.
Morgan Kaufmann Publishers Inc.Google Scholar Count in October 2006: 6907
#2. CART
L. Breiman, J. Friedman, R. Olshen, and C. Stone. Classification and
Regression Trees. Wadsworth, Belmont, CA, 1984.Google Scholar Count in October 2006: 6078
#3. K Nearest Neighbours (kNN)
Hastie, T. and Tibshirani, R. 1996. Discriminant Adaptive Nearest
Neighbor Classification. IEEE Trans. PatternAnal. Mach. Intell. (TPAMI). 18, 6 (Jun. 1996), 607-616.DOI= http://dx.doi.org/10.1109/34.506411Google Scholar Count: 183
#4. Naive Bayes
Hand, D.J., Yu, K., 2001. Idiot's Bayes: Not So Stupid After All?
Internat. Statist. Rev. 69, 385-398.Google Scholar Count in October 2006: 51
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Statistical Learning
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#5. SVM
Vapnik, V. N. 1995. The Nature of Statistical Learning
Theory. Springer-Verlag New York, Inc.Google Scholar Count in October 2006: 6441
#6. EM
McLachlan, G. and Peel, D. (2000). Finite Mixture Models.
J. Wiley, New York.Google Scholar Count in October 2006: 848
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Association Analysis
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#7. Apriori
Rakesh Agrawal and Ramakrishnan Srikant. Fast Algorithms for Mining
Association Rules. In Proc. of the 20th Int'l Conference on Very LargeDatabases (VLDB '94), Santiago, Chile, September 1994.http://citeseer.comp.nus.edu.sg/agrawal94fast.htmlGoogle Scholar Count in October 2006: 3639
#8. FP-Tree
Han, J., Pei, J., and Yin, Y. 2000. Mining frequent patterns without
candidate generation. In Proceedings of the 2000 ACM SIGMODinternational Conference on Management of Data (Dallas, Texas, UnitedStates, May 15 - 18, 2000). SIGMOD '00. ACM Press, New York, NY, 1-12.DOI= http://doi.acm.org/10.1145/342009.335372Google Scholar Count in October 2006: 1258
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Link Mining
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#9. PageRank
Brin, S. and Page, L. 1998. The anatomy of a large-scale hypertextual
Web search engine. In Proceedings of the Seventh internationalConference on World Wide Web (WWW-7) (Brisbane,Australia). P. H. Enslow and A. Ellis, Eds. Elsevier SciencePublishers B. V., Amsterdam, The Netherlands, 107-117.DOI= http://dx.doi.org/10.1016/S0169-7552(98)00110-XGoogle Shcolar Count: 2558
#10. HITS
Kleinberg, J. M. 1998. Authoritative sources in a hyperlinked
environment. In Proceedings of the Ninth Annual ACM-SIAM Symposium onDiscrete Algorithms (San Francisco, California, United States, January25 - 27, 1998). Symposium on Discrete Algorithms. Society forIndustrial and Applied Mathematics, Philadelphia, PA, 668-677.Google Shcolar Count: 2240
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Clustering
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#11. K-Means
MacQueen, J. B., Some methods for classification and analysis of
multivariate observations, in Proc. 5th Berkeley Symp. MathematicalStatistics and Probability, 1967, pp. 281-297.Google Scholar Count in October 2006: 1579
#12. BIRCH
Zhang, T., Ramakrishnan, R., and Livny, M. 1996. BIRCH: an efficient
data clustering method for very large databases. In Proceedings of the1996 ACM SIGMOD international Conference on Management of Data(Montreal, Quebec, Canada, June 04 - 06, 1996). J. Widom, Ed.SIGMOD '96. ACM Press, New York, NY, 103-114.DOI= http://doi.acm.org/10.1145/233269.233324Google Scholar Count in October 2006: 853
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Bagging and Boosting
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#13. AdaBoost
Freund, Y. and Schapire, R. E. 1997. A decision-theoretic
generalization of on-line learning and an application toboosting. J. Comput. Syst. Sci. 55, 1 (Aug. 1997), 119-139.DOI= http://dx.doi.org/10.1006/jcss.1997.1504Google Scholar Count in October 2006: 1576
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Sequential Patterns
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#14. GSP
Srikant, R. and Agrawal, R. 1996. Mining Sequential Patterns:
Generalizations and Performance Improvements. In Proceedings of the5th international Conference on Extending Database Technology:Advances in Database Technology (March 25 - 29, 1996). P. M. Apers,M. Bouzeghoub, and G. Gardarin, Eds. Lecture Notes In ComputerScience, vol. 1057. Springer-Verlag, London, 3-17.Google Scholar Count in October 2006: 596
#15. PrefixSpanJ. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal and
M-C. Hsu. PrefixSpan: Mining Sequential Patterns Efficiently byPrefix-Projected Pattern Growth. In Proceedings of the 17thinternational Conference on Data Engineering (April 02 - 06,2001). ICDE '01. IEEE Computer Society, Washington, DC.Google Scholar Count in October 2006: 248
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Integrated Mining
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#16. CBA
Liu, B., Hsu, W. and Ma, Y. M. Integrating classification and
association rule mining. KDD-98, 1998, pp. 80-86.http://citeseer.comp.nus.edu.sg/liu98integrating.htmlGoogle Scholar Count in October 2006: 436
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Rough Sets
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#17. Finding reduct
Zdzislaw Pawlak, Rough Sets: Theoretical Aspects of Reasoning about
Data, Kluwer Academic Publishers, Norwell, MA, 1992Google Scholar Count in October 2006: 329
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Graph Mining
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#18. gSpan
Yan, X. and Han, J. 2002. gSpan: Graph-Based Substructure Pattern
Mining. In Proceedings of the 2002 IEEE International Conference onData Mining (ICDM '02) (December 09 - 12, 2002). IEEE ComputerSociety, Washington, DC.