Classification
==================================
#1. C4.5
Quinlan, J. R. 1993. C4.5: Programs for Machine Learning.
Morgan Kaufmann Publishers Inc.
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#2. CART
L. Breiman, J. Friedman, R. Olshen, and C. Stone. Classification and
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#3. K Nearest Neighbours (kNN)
Hastie, T. and Tibshirani, R. 1996. Discriminant Adaptive Nearest
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#4. Naive Bayes
Hand, D.J., Yu, K., 2001. Idiot's Bayes: Not So Stupid After All?
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==================================
Statistical Learning
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#5. SVM
Vapnik, V. N. 1995. The Nature of Statistical Learning
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#6. EM
McLachlan, G. and Peel, D. (2000). Finite Mixture Models.
J. Wiley, New York.
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Association Analysis
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#7. Apriori
Rakesh Agrawal and Ramakrishnan Srikant. Fast Algorithms for Mining
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#8. FP-Tree
Han, J., Pei, J., and Yin, Y. 2000. Mining frequent patterns without
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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 international
Conference on World Wide Web (WWW-7) (Brisbane,
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#10. HITS
Kleinberg, J. M. 1998. Authoritative sources in a hyperlinked
environment. In Proceedings of the Ninth Annual ACM-SIAM Symposium on
Discrete Algorithms (San Francisco, California, United States, January
25 - 27, 1998). Symposium on Discrete Algorithms. Society for
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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. Mathematical
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#12. BIRCH
Zhang, T., Ramakrishnan, R., and Livny, M. 1996. BIRCH: an efficient
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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 to
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Sequential Patterns
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#14. GSP
Srikant, R. and Agrawal, R. 1996. Mining Sequential Patterns:
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#15. PrefixSpan
J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal and
M-C. Hsu. PrefixSpan: Mining Sequential Patterns Efficiently by
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Integrated Mining
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#16. CBA
Liu, B., Hsu, W. and Ma, Y. M. Integrating classification and
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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, 1992
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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 on
Data Mining (ICDM '02) (December 09 - 12, 2002). IEEE Computer
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