An Evaluation of Approaches to Classification Rule Selection

Brighton, United Kingdom November 01-November 04

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http://doi.ieeecomputersociety.org/10.1109/ICDM.2004.10012

Fourth IEEE International Conference ...

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	ASCII Text	x
	Frans Coenen, Paul Leng, "An Evaluation of Approaches to Classification Rule Selection," Data Mining, IEEE International Conference on, pp. 359-362, Fourth IEEE International Conference on Data Mining (ICDM'04), 2004.

	BibTex	x
	@article{ 10.1109/ICDM.2004.10012, author = {Frans Coenen and Paul Leng}, title = {An Evaluation of Approaches to Classification Rule Selection}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2004}, isbn = {0-7695-2142-8}, pages = {359-362}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2004.10012}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - An Evaluation of Approaches to Classification Rule Selection SN - 0-7695-2142-8 SP359 EP362 A1 - Frans Coenen, A1 - Paul Leng, PY - 2004 KW - Classification rule evaluation measures VL - 0 JA - Data Mining, IEEE International Conference on ER -

Frans Coenen, The University of Liverpool, UK

Paul Leng, The University of Liverpool, UK

In this paper a number of Classification Rule evaluation measures are considered. In particular the authors review the use of a variety of selection techniques used to order classification rules contained in a classifier, and a number of mechanisms used to classify unseen data. The authors demonstrate that rule ordering founded on the size of antecedent works well given certain conditions.

Index Terms:

Classification rule evaluation measures

Citation:

Frans Coenen, Paul Leng, "An Evaluation of Approaches to Classification Rule Selection," icdm, pp.359-362, Fourth IEEE International Conference on Data Mining (ICDM'04), 2004

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