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Kanal L. N., Patterns in pattern recognition: 1968-1974.
IEEE Transactions on
Information Theory
IT-20 6:697-722, 1974.
Kargupta H., and Chan P. (eds.),
Advances in Distributed and Parallel Knowledge
Discovery
, pp. 185-210, Portland OR: AAAI/MIT Press, 2000.
Kaufman L., and Rousseeuw P. J., Clustering by means of medoids, In
Statistical
Data Analysis, based on the L1 Norm
, Y. Dodge (ed.), pp. 405-416,
Amsterdam: Elsevier/North Holland, 1987.
Kaufman L., and Rousseeuw P. J.,
Finding Groups in Data
, New-York: Wiley,
1990.
Kass G. V., An exploratory technique for investigating large quantities of
categorical data,
Applied Statistics
29(2):119-127, 1980.
Kearns M., and Mansour Y., A fast, bottom-up decision tree pruning algorithm
with near-optimal generalization, In
Machine Learning: Proceedings of the
Fifteenth International Conference
, J. Shavlik (ed.), pp. 269-277, Morgan
Kaufmann Publishers, Inc., 1998.
Kearns M., and Mansour Y., On the boosting ability of top-down decision tree
learning algorithms.
Journal of Computer and Systems Sciences
58(1):109-
128, 1999.
Kenney J. F., and Keeping E. S., Moment-Generating and Characteristic
Functions, Some Examples of Moment-Generating Functions, and Unique-
ness Theorem for Characteristic Functions, x4.6-4.8, In
Mathematics of
Statistics
, Pt. 2, 2nd edn. pp. 72-77, Princeton, NJ: Van Nostrand, 1951.
Kerber R., ChiMerge: Descretization of numeric attributes, In AAAI-92,
Pro-
ceedings Ninth National Conference on Artificial Intelligence
, pp. 123-128,
AAAI Press/MIT Press, 1992.
Kim J. O., and Mueller C. W.,
Factor Analysis: Statistical Methods and Practical
Issues
, Sage Publications, 1978.
Kim D. J., Park Y. W., and Park D.-J., A novel validity index for determination of
the optimal number of clusters,
IEICE Trans. Inf.
E84-D(2):281-285, 2001.
King B., Step-wise clustering procedures,
Journal of American Statistical Asso-
ciation
69:86-101, 1967.
Kira K., and Rendell L. A., A practical approach to feature selection. In
Machine
Learning: Proceedings of the Ninth International Conference
, 1992.
Klosgen W., and Zytkow J. M., KDD: The purpose, necessity and chalanges, In
Handbook of Data Mining and Knowledge Discovery
,W.KlosgenandJ.M.
Zytkow (eds.), pp. 1-9, Oxford: Oxford University Press, 2002.
Kohavi R., Bottom-up induction of oblivious read-once decision graphs, In
Proc.
European Conference on Machine Learning
, F. Bergadano and L. De Raedt
(eds.), pp. 154-169, Springer-Verlag, 1994.
Kohavi R., Scaling up the accuracy of naive-bayes classifiers: A decision-tree
hybrid, In
Proceedings of the Second International Conference on Knowledge
Discovery and Data Mining
, pp. 114-119, 1996.
Kohavi R., Becker B., and Sommerfield D., Improving simple Bayes, In
Proceed-
ings of the European Conference on Machine Learning
, 1997.
Kohavi R., and John G., The wrapper approach, In
Feature Extraction, Con-
struction and Selection: A Data Mining Perspective
,H.LiuandH.Motoda
(eds.), Kluwer Academic Publishers, 1998.
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