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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/5757

Title: Dilated Chi-square: a novel interestingness measure to build accurate and compact decision list
Authors: Lan, Y.
Chen, G.
Janssens, D.
WETS, Geert
Issue Date: 2004
Publisher: SPRINGER
Citation: Shi, Z & He, Q (Ed.) INTELLIGENT INFORMATION PROCESSING II. p. 233-238.
Series/Report: INTERNATIONAL FEDERATION FOR INFORMATION PROCESSING, 163
Abstract: Associative classification has aroused significant attention in recent years. This paper proposed a novel interestingness measure, named dilated chi-square, to statistically reveal the interdependence between the antecedents and the consequent of classification rules. Using dilated chi-square, instead of confidence, as the primary ranking criterion for rules under the framework of popular CBA algorithm, the adapted algorithm presented in this paper can empirically generate more accurate and much more compact decision lists.
URI: http://hdl.handle.net/1942/5757
DOI: 10.1007/0-387-23152-8_30
ISI #: 000225784400030
ISBN: 0-387-23151-X
ISSN: 1571-5736
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2006
Appears in Collections: Research publications

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