Abstract
Based upon the predictive association measure λ by Goodman and Kruskal, a new algorithm for the induction of a decision tree is proposed. This algorithm cares about the asymmetric character of the classification task and enables the use of statistical inference.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
BREIMAN, L.; FRIEDMAN, J.H.; Olshen, R.A., and STONE, C.J. (1984): Classification and Regression Tree. Statistics Series. Wadsworth, Belmont.
GOODMAN, L.A. and KRUSKAL, W.H. (1954): Measures of Association for Cross Classifications. Journal of the American Statistical Association, 49, 732–764.
GOODMAN, L.A. and KRUSKAL, W.H. (1963): Measures of Association for Cross Classifications, III: Approximate Sampling Theory. Journal of the American Statistical Association, Vol. 58, 310–364.
GUTTMAN, L. (1941): An Outline of the Statistical Theory of Prediction. In: Horst, P. (Ed.): The Prediction of Personal Adjustment. Bulletin 48, Social Science Research Council, New York.
HAN, J. and KAMBER, M. (2001): Data Mining. Concepts and Techniques. Morgan Kaufmann, San Francisco.
HILBERT, A. (1998): Zur Theorie der Korrelationsmaße. Eul Verlag, Lohmar, Köln.
HILBERT, A. (2002): Some Remarks about the Usage of Asymmetric Correlation Measurements for the Induction of Decision Trees. Arbeitspapiere zur Mathematischen Wirts chaftsforschung, Universität Augsburg, Heft 180.
KAAS, G.V. (1980): An Exploratory Technique for Investigating Large Quantities of Categorical Data. Applied Statistics, 29, No. 2, 119–127.
MESSENGER, R.C. and MANDELL, L.M. (1972): A modal search technique for predictive nominal scale multivariate analysis. Journal of the American Statistical Society, 67, 768–772.
QUINLAN, J.R. (1986): Induction of Decision Trees. Machine Learning, 1, 81–106.
QUINLAN, J.R. (1993): C4.5 Programs for Machine Learning. Morgan Kaufmann, San Mateo, California.
SHANNON, C.E. (1948): The Mathematical Theory of Communication. The Bell Systems Technical Journal, Vol. 27, 379–423.
SONQUIST, J.A.; BAKER, E.L. and MORGAN, J.N. (1971): Searching for Structure. Institute for Social Research, University of Michigan, Ann Arbor, MI.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hilbert, A. (2003). ASCAID: Using an Asymmetric Correlation Measure for Automatic Interaction Detection. In: Schader, M., Gaul, W., Vichi, M. (eds) Between Data Science and Applied Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18991-3_51
Download citation
DOI: https://doi.org/10.1007/978-3-642-18991-3_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40354-8
Online ISBN: 978-3-642-18991-3
eBook Packages: Springer Book Archive