数据挖掘经典算法

     Apriori,FP-Tree这两个关联规则算法曾经为了学习序列模式挖掘算法，看了一段时间，因为关于深度优先的一系列算法（比如GSP）都是基于Apriori规则的。个人觉得，GSP其实是在原关联规则上考虑时间因素，即分析顾客在一定时期内的购买趋势。

  

 

      Classification
==============
#1. C4.5
Quinlan, J. R. 1993. C4.5: Programs for Machine Learning.
Morgan Kaufmann Publishers Inc.

#2. CART
L. Breiman, J. Friedman, R. Olshen, and C. Stone. Classification and
Regression Trees. Wadsworth, Belmont, CA, 1984.
#3. K Nearest Neighbours (kNN)
Hastie, T. and Tibshirani, R. 1996. Discriminant Adaptive Nearest
Neighbor Classification. IEEE Trans. Pattern
Anal. Mach. Intell. (TPAMI). 18, 6 (Jun. 1996), 607-616.
DOI= http://dx.doi.org/10.1109/34.506411
#4. Naive Bayes
Hand, D.J., Yu, K., 2001. Idiot's Bayes: Not So Stupid After All?
Internat. Statist. Rev. 69, 385-398.

Statistical Learning
====================
#5. SVM
Vapnik, V. N. 1995. The Nature of Statistical Learning
Theory. Springer-Verlag New York, Inc.
#6. EM
McLachlan, G. and Peel, D. (2000). Finite Mixture Models.
J. Wiley, New York.

Association Analysis
====================
#7. Apriori
Rakesh Agrawal and Ramakrishnan Srikant. Fast Algorithms for Mining
Association Rules. In Proc. of the 20th Int'l Conference on Very Large
Databases (VLDB '94), Santiago, Chile, September 1994.
http://citeseer.comp.nus.edu.sg/agrawal94fast.html
#8. FP-Tree
Han, J., Pei, J., and Yin, Y. 2000. Mining frequent patterns without
candidate generation. In Proceedings of the 2000 ACM SIGMOD
international Conference on Management of Data (Dallas, Texas, United
States, May 15 - 18, 2000). SIGMOD '00. ACM Press, New York, NY, 1-12.
DOI= http://doi.acm.org/10.1145/342009.335372

Link Mining
===========
#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,
Australia). P. H. Enslow and A. Ellis, Eds. Elsevier Science
Publishers B. V., Amsterdam, The Netherlands, 107-117.
DOI= http://dx.doi.org/10.1016/S0169-7552(98)00110-X
#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
Industrial and Applied Mathematics, Philadelphia, PA, 668-677.

Clustering
==========
#11. K-Means
MacQueen, J. B., Some methods for classification and analysis of
multivariate observations, in Proc. 5th Berkeley Symp. Mathematical
Statistics and Probability, 1967, pp. 281-297.
#12. BIRCH
Zhang, T., Ramakrishnan, R., and Livny, M. 1996. BIRCH: an efficient
data clustering method for very large databases. In Proceedings of the
1996 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/10.1145/233269.233324

Bagging and Boosting
====================
#13. AdaBoost
Freund, Y. and Schapire, R. E. 1997. A decision-theoretic
generalization of on-line learning and an application to
boosting. J. Comput. Syst. Sci. 55, 1 (Aug. 1997), 119-139.
DOI= http://dx.doi.org/10.1006/jcss.1997.1504

Sequential Patterns
===================
#14. GSP
Srikant, R. and Agrawal, R. 1996. Mining Sequential Patterns:
Generalizations and Performance Improvements. In Proceedings of the
5th 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 Computer
Science, vol. 1057. Springer-Verlag, London, 3-17.
#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
Prefix-Projected Pattern Growth. In Proceedings of the 17th
international Conference on Data Engineering (April 02 - 06,
2001). ICDE '01. IEEE Computer Society, Washington, DC.

Integrated Mining
=================
#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.html

Rough Sets
==========
#17. Finding reduct
Zdzislaw Pawlak, Rough Sets: Theoretical Aspects of Reasoning about
Data, Kluwer Academic Publishers, Norwell, MA, 1992

Graph Mining
============
#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
Society, Washington, DC.

------------------------------以上18个算法介绍转自：www.chinakdd.com 数据挖掘研究院