Databases Reference
In-Depth Information
[LV88]
W. Y. Loh and N. Vanichsetakul. Tree-structured classificaiton via generalized discrimi-
nant analysis. J. American Statistical Association , 83:715-728, 1988.
[LZ05]
Z. Li and Y. Zhou. PR-Miner: Automatically extracting implicit programming rules
and detecting violations in large software code. In Proc. 2005 ACM SIGSOFT Symp.
Foundations of Software Engineering (FSE'05) , Lisbon, Portugal, Sept. 2005.
[MA03]
S. Mitra and T. Acharya. Data Mining: Multimedia, Soft Computing, and Bioinformatics .
John Wiley & Sons, 2003.
[MAE05]
A. Metwally, D. Agrawal, and A. El Abbadi. Efficient computation of frequent and
top- k elements in data streams. In Proc. 2005 Int. Conf. Database Theory (ICDT'05) ,
pp. 398-412, Edinburgh, Scotland, Jan. 2005.
[Mac67]
J. MacQueen. Some methods for classification and analysis of multivariate observations.
In Proc. 5th Berkeley Symp. Math. Stat. Prob. , 1:281-297, Berkeley, CA, 1967.
[Mag94]
J. Magidson. The CHAID approach to segmentation modeling: CHI-squared automatic
interaction detection. In R. P. Bagozzi (ed.), Advanced Methods of Marketing Research ,
pp. 118-159. Blackwell Business, 1994.
[Man00]
H. Mannila. Theoretical frameworks of data mining. SIGKDD Explorations , 1:30-32,
2000.
[MAR96]
M. Mehta, R. Agrawal, and J. Rissanen. SLIQ: A fast scalable classifier for data mining.
In Proc. 1996 Int. Conf. Extending Database Technology (EDBT'96) , pp. 18-32, Avignon,
France, Mar. 1996.
[Mar09]
S. Marsland. Machine Learning: An Algorithmic Perspective . Chapman & Hall/CRC, 2009.
[MB88]
G. J. McLachlan and K. E. Basford.
Mixture Models: Inference and Applications to
Clustering . John Wiley & Sons, 1988.
[MC03] M. V. Mahoney and P. K. Chan. Learning rules for anomaly detection of hostile net-
work traffic. In Proc. 2003 Int. Conf. Data Mining (ICDM'03) , Melbourne, FL, Nov.
2003.
[MCK C 04] N. Mamoulis, H. Cao, G. Kollios, M. Hadjieleftheriou, Y. Tao, and D. Cheung. Min-
ing, indexing, and querying historical spatiotemporal data. In Proc. 2004 ACM SIGKDD
Int. Conf. Knowledge Discovery in Databases (KDD'04) , pp. 236-245, Seattle, WA, Aug.
2004.
[MCM83]
R. S. Michalski, J. G. Carbonell, and T. M. Mitchell. Machine Learning, An Artificial
Intelligence Approach , Vol. 1. Morgan Kaufmann, 1983.
[MCM86]
R. S. Michalski, J. G. Carbonell, and T. M. Mitchell. Machine Learning, An Artificial
Intelligence Approach , Vol. 2. Morgan Kaufmann, 1986.
[MD88]
M. Muralikrishna and D. J. DeWitt. Equi-depth histograms for extimating selectiv-
ity factors for multi-dimensional queries.
In Proc.
1988 ACM-SIGMOD Int.
Conf.
Management of Data (SIGMOD'88) , pp. 28-36, Chicago, IL, June 1988.
[Mei03]
M. Meila. Comparing clusterings by the variation of information. In Proc. 16th Annual
Conf. Computational Learning Theory (COLT'03) , pp. 173-187, Washington, DC, Aug.
2003.
[Mei05]
M. Meila. Comparing clusterings: An axiomatic view. In Proc. 22nd Int. Conf. Machine
Learning (ICML'05) , pp. 577-584, Bonn, Germany, 2005.
[Men03]
J. Mena. Investigative Data Mining with Security and Criminal Detection . Butterworth-
Heinemann, 2003.
 
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