1Gehrke J, Ramakrishnan R, Ganti V. Rainforest a framework for fast decision tree construction of large datasets[A]. In VLDB[C].1998.
2Friedman N, Geiger D, Goldszmidt M. Bayesian network classifier [J]. Machine L earning, 1997, 29(1): 131-163.
3Liu B, Hsu W, Ma Y. Integrating classification and association rule mining[A]. Proc of the 4th int confon knowle-dge discovery and dataMining[C]. NY, USA:AAAIPress, 1998.80-86.
4WANG M, Iyer B, Vitter J S. Scalable mining for classification rules in relational databases[A]. Eaglestone B, DesaiBC, SHAO Jianhua. Proc of the 1998 Int database eng and appl symp[C].Cardiff, Wales, UK:IEEEComputer Society, 1998.58-67.
5MacQueen J. Some methods for classification and analysis of multivariate observations[A].Proc 5th berkeley symp.math statist[C]. Prob, 1967-01.
6Kaufman L, Rousseeuw P J. Finding groups in data: an introduction to cluster analysis[M]. John Wiley and Sons, 1990.
7Wei Wang, Jiong Yang, Richard Muntz. STING: A statistical information grid approach to spatial data mining[A]. Twenty-third international conference on very large data bases[C], 1997.
8Sheikholeslami G, Chatterjee S, Zhang A. Wave cluster: a multiresolution clustering approach for very large spatial databases [A]. Proc. Int. Conf. on very large data bases[C]. New York, NY,1998.428-439.
9Agrawal R, Gehrke J, Gunopulos D. Automatic subspace clustering of high dimensional data for data mining applications[A].Proc. ACM SIGMOD int. conf. on management of data[C]. Seattle, WA, 1998.94-105.
10Han J, Kambr M. Data mining:Concepts and techniques[M].Beijing Higher Education Press, 2001.1-3.
