Abstract
Induction graphs, which are a generalization of decision trees, have a special place among the methods of Data Mining. Indeed, they generate lattice graphs instead of trees. They perform well, are capable of handling data in large volumes, are relatively easy for a non-specialist to interpret, and are applicable without restriction on data of any type (qualitative, quantitative). The explosion of softwares based on the paradigm of decision trees and more generally induction graphs is a rather strong evidence of their success. In this article, we present a complete method of induction graphs; the method SIPINA.
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
AURAY, J.P., DURU, G. and ZIGHED D.A. (1991): Analyse des données multidimensionnelles: les méthodes d’explication. Editions A. Lacassagne, Lyon.
BERTIER, P. and BOUROCHE, J.M. (1981): Analyse des données multidimensionnelles. Presses Universitaires de France.
BOUROCHE, J.P. and TENENHAUS, M. (1970) Quelques méthodes de segmentation. RAIRO 42, 29–42.
BREIMAN, L., FRIEDMAN, J.H., OLSHEN, R.A. and STONE, C.J. (1984): Classification and Regression Trees. California: Wadsworth International.
CIAMPI, A., HOGG, S.A., McKINNEY, S. and THIFFAULT, J. (1988): RECPAM: a computer program for recursive partition and amalgamation for censored survival data and other situations frequently occurring in biostatistics I. Methods and program Features. Computer Methods and Programs in Biomedicine 26, 239–256
CIAMPI, A., THIFFAULT, J. and SAGMAN, U. (1989): RECPAM: a computer program for recursive partition and amalgamation for censored survival data and other situations frequently occurring in biostatistics II. Applications to data on small cell carcinoma of the lung. Computer Methods and Programs in Biomedicine 30, 239–256
DUDA, R.O. and HART, P.E. (1973): Pattern Classification and Scene Analysis. Wiley, N.Y.
DEVIJVER, P. and KITTLER, J. (1982): Pattern Recognition: A Statistical Approach. Prentice Hall.
LAUMON, B. (1979): Une méthode de reconnaissance de formes pour l’estimation d’une variable continue: application à la docimologie. PhD thesis, University of Lyon.
MORGAN, J. N. and SONQUIST, J. A. (1963): Problems in the analysis of survey data, and a proposal. Journ. Amer. Stat. Assoc. 58, 415–434.
PICARD, C. (1965): Théorie des questionnaires. Les grands problèmes des sciences. Gauthier-Villard.
QUINLAN, J.R. (1993): C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, CA.
QUINLAN, J.R. (1979): Discovering rules by induction from large collections of examples. In: D. Michie (Ed.): Expert Systems in Micro Electronic Age. Edinburgh University Press, 168–201.
QUINLAN, J.R. (1986): Induction of decision trees. Machine Learning 1, 81–106.
ROUTHIER, J.L. (1978): Un processus d’interrogation latticiel: application á l’aide au diagnostic sur les nodules thyroidiens froids. PhD thesis, University of Lyon 2.
TERRENOIRE, M. (1970): Un modèle mathématique de processus d’interrogation: les pseudoquestionnaires. PhD thesis, University of Grenoble.
TOUNISSOUX, D. (1974): Pseudoquestionnaires et information. Dissertation 3rd cycle, University of Lyon 1.
TOUNISSOUX, D. (1980): Processus séquentiels adaptatifs de reconnaissance de Formes pour l’aide au diagnostic. PhD thesis, University Claude Bernard-Lyon 1.
WALD, A. (1947): Sequential Analysis. Wiley.
ZIGHED, D.A. (1985): Méthodes et outils pour les processus d’interrogation non arborescents. PhD thesis, University Claude Bernard-Lyon 1.
ZIGHED, D.A., AURAY, J. P. and DURU G. (1992): SIPINA: Méthode et logiciel. Lacassagne.
ZIGHED, D.A. and RAKOTOMALALA R. (2000): Graphes d’Induction: Apprentissage Automatique et Data Mining. Hermès, Paris.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Zighed, D.A. (2007). Induction Graphs for Data Mining. In: Brito, P., Cucumel, G., Bertrand, P., de Carvalho, F. (eds) Selected Contributions in Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73560-1_39
Download citation
DOI: https://doi.org/10.1007/978-3-540-73560-1_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73558-8
Online ISBN: 978-3-540-73560-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)