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Hybrid classification - using axis-parallel and oblique subdivisions of the attribute space

Hybride Klassifikation - Benutzung achsenparalleler und schiefer Unterteilungen des Attributraumes
: Schulmeister, B.; Bleich, M.

Lavrac, N.; Wrobel, S.:
Machine learning. 8th European Conference on Machine Learning : Heraclion, Crete, Greece, April 25 - 27, 1995. Proceedings
Berlin: Springer, 1995 (Lecture Notes in Computer Science 912 : Lecture Notes in Artificial Intelligence)
ISBN: 3-540-59286-5
ISSN: 0302-9743
European Conference on Machine Learning (ECML) <8, 1995, Heraklion>
Conference Paper
Fraunhofer IITB, Außenstelle Prozessoptimierung (EPO); 1997
classification; decision tree; Entscheidungsbaum; Klassifikation; machine learning; maschinelles Lernen

This paper describes the hybrid algorithm DIPOL-DT which uses the strengths of standard decision tree algorithms and piecewise linear classifiers because at every level of learning it chooses the appropriate subdivision of the attribute space: a split with hyperplanes in general position or an axis-parallel split. The proposed method combines two existing algorithms - the piecewise linear classification algorithm DIPOL and the decision tree algorithm CAL5. To some extent the strength of each individual method complements the weaknesses of the other.