Local modelling in classification.

Gero Szepannek; Julia Schiffner; Julie C. Wilson; Claus Weihs; Petra Perner

doi:10.1007/978-3-540-70720-2_12

Local modelling in classification.

Gero Szepannek, Julia Schiffner, Julie C. Wilson, Claus Weihs, Petra Perner (Editor)

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

Abstract

In classification tasks it may sometimes not be meaningful to build single rules on the whole data. This may especially be the case if the classes are composed of several subclasses. Several common as well as recent issues are presented to solve this problem. As it can e.g. be seen in Weihs et al. (2006) there may result strong benefit from such local modelling. All presented methods are evaluated and compared on four real-world classification problems in order to obtain some overall ranking of their performance following an idea of Hornik and Meyer (2007).

Original language	English
Title of host publication	Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Subtitle of host publication	Proceedings of 8th Industrial Conference, ICDM 2008
Publisher	Springer
Pages	153-164
Number of pages	12
Volume	5077
Edition	2008
DOIs	https://doi.org/10.1007/978-3-540-70720-2_12
Publication status	Published - 2008

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	5077

Access to Document

10.1007/978-3-540-70720-2_12

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Szepannek, G., Schiffner, J., Wilson, J. C., Weihs, C., & Perner, P. (Ed.) (2008). Local modelling in classification. In Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects: Proceedings of 8th Industrial Conference, ICDM 2008 (2008 ed., Vol. 5077, pp. 153-164). (Lecture Notes in Computer Science; Vol. 5077). Springer. https://doi.org/10.1007/978-3-540-70720-2_12

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Szepannek, G, Schiffner, J, Wilson, JC, Weihs, C & Perner, P (ed.) 2008, Local modelling in classification. in Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects: Proceedings of 8th Industrial Conference, ICDM 2008. 2008 edn, vol. 5077, Lecture Notes in Computer Science, vol. 5077, Springer, pp. 153-164. https://doi.org/10.1007/978-3-540-70720-2_12

Local modelling in classification. / Szepannek, Gero; Schiffner, Julia; Wilson, Julie C. et al.
Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects: Proceedings of 8th Industrial Conference, ICDM 2008. Vol. 5077 2008. ed. Springer, 2008. p. 153-164 (Lecture Notes in Computer Science; Vol. 5077).

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

TY - CHAP

T1 - Local modelling in classification.

AU - Szepannek, Gero

AU - Schiffner, Julia

AU - Wilson, Julie C.

AU - Weihs, Claus

A2 - Perner, Petra

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AB - In classification tasks it may sometimes not be meaningful to build single rules on the whole data. This may especially be the case if the classes are composed of several subclasses. Several common as well as recent issues are presented to solve this problem. As it can e.g. be seen in Weihs et al. (2006) there may result strong benefit from such local modelling. All presented methods are evaluated and compared on four real-world classification problems in order to obtain some overall ranking of their performance following an idea of Hornik and Meyer (2007).

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T3 - Lecture Notes in Computer Science

SP - 153

EP - 164

BT - Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects

PB - Springer

ER -

Local modelling in classification.

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