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Soft Computing

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01-04-2012 | Original Paper

OFP_CLASS: a hybrid method to generate optimized fuzzy partitions for classification

Authors: Jose M. Cadenas, M. Carmen Garrido, Raquel Martínez, Piero P. Bonissone

Published in: Soft Computing | Issue 4/2012

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Abstract

The discretization of values plays a critical role in data mining and knowledge discovery. The representation of information through intervals is more concise and easier to understand at certain levels of knowledge than the representation by mean continuous values. In this paper, we propose a method for discretizing continuous attributes by means of fuzzy sets, which constitute a fuzzy partition of the domains of these attributes. This method carries out a fuzzy discretization of continuous attributes in two stages. A fuzzy decision tree is used in the first stage to propose an initial set of crisp intervals, while a genetic algorithm is used in the second stage to define the membership functions and the cardinality of the partitions. After defining the fuzzy partitions, we evaluate and compare them with previously existing ones in the literature.

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Title: OFP_CLASS: a hybrid method to generate optimized fuzzy partitions for classification
Authors: Jose M. Cadenas
M. Carmen Garrido
Raquel Martínez
Piero P. Bonissone
Publication date: 01-04-2012
Publisher: Springer-Verlag
Published in: Soft Computing / Issue 4/2012
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-011-0778-0

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