Handling continuous-valued attributes in decision tree with neural network modeling

Dae Eun Kim; Jaeho Lee

doi:10.1007/3-540-45164-1_22

Handling continuous-valued attributes in decision tree with neural network modeling

Dae Eun Kim, Jaeho Lee

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

13 Citations (Scopus)

Abstract

Induction tree is useful to obtain a proper set of rules for a large amount of examples. However, it has difficulty in obtaining the relation between continuous-valued data points. Many data sets show significant correlations between input variables, and a large amount of useful information is hidden in the data as nonlinearities. It has been shown that neural network is better than direct application of induction tree in modeling nonlinear characteristics of sample data. It is proposed in this paper that we derive a compact set of rules to support data with input variable relations. Those relations as a set of linear classifiers can be obtained from neural network modeling based on back-propagation. This will also solve overgeneralization amd overspecialization problems often seen in induction tree. We have tested this scheme over several data sets to compare with decision tree results.

Original language	English
Title of host publication	Machine Learning
Subtitle of host publication	ECML 2000 - 11th European Conference on Machine Learning, Proceedings
Editors	Ramon Lopez de Mantaras, Enric Plaza
Publisher	Springer Verlag
Pages	211-219
Number of pages	9
ISBN (Print)	9783540451648
DOIs	https://doi.org/10.1007/3-540-45164-1_22
Publication status	Published - 2000
Event	11th European Conference on Machine Learning, ECML 2000 - Barcelona, Catalonia, Spain Duration: 2000 May 31 → 2000 Jun 2

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1810
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	11th European Conference on Machine Learning, ECML 2000
Country/Territory	Spain
City	Barcelona, Catalonia
Period	00/5/31 → 00/6/2

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2000.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/3-540-45164-1_22

Cite this

Kim, D. E., & Lee, J. (2000). Handling continuous-valued attributes in decision tree with neural network modeling. In R. L. de Mantaras, & E. Plaza (Eds.), Machine Learning: ECML 2000 - 11th European Conference on Machine Learning, Proceedings (pp. 211-219). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1810). Springer Verlag. https://doi.org/10.1007/3-540-45164-1_22

Kim, Dae Eun ; Lee, Jaeho. / Handling continuous-valued attributes in decision tree with neural network modeling. Machine Learning: ECML 2000 - 11th European Conference on Machine Learning, Proceedings. editor / Ramon Lopez de Mantaras ; Enric Plaza. Springer Verlag, 2000. pp. 211-219 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Kim, DE & Lee, J 2000, Handling continuous-valued attributes in decision tree with neural network modeling. in RL de Mantaras & E Plaza (eds), Machine Learning: ECML 2000 - 11th European Conference on Machine Learning, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1810, Springer Verlag, pp. 211-219, 11th European Conference on Machine Learning, ECML 2000, Barcelona, Catalonia, Spain, 00/5/31. https://doi.org/10.1007/3-540-45164-1_22

Handling continuous-valued attributes in decision tree with neural network modeling. / Kim, Dae Eun; Lee, Jaeho.
Machine Learning: ECML 2000 - 11th European Conference on Machine Learning, Proceedings. ed. / Ramon Lopez de Mantaras; Enric Plaza. Springer Verlag, 2000. p. 211-219 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1810).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Kim DE, Lee J. Handling continuous-valued attributes in decision tree with neural network modeling. In de Mantaras RL, Plaza E, editors, Machine Learning: ECML 2000 - 11th European Conference on Machine Learning, Proceedings. Springer Verlag. 2000. p. 211-219. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45164-1_22

Handling continuous-valued attributes in decision tree with neural network modeling

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