Interpretability-preserving genetic optimization of linguistic terms in fuzzy models for fuzzy ordered classification: An ecological case study

  • Authors:

  • Ester Van Broekhoven;Veronique Adriaenssens;Bernard De Baets

  • Affiliations:

  • Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure links 653, B-9000 Gent, Belgium;Department of Applied Ecology and Environmental Biology, Ghent University, Jozef Plateaustraat 22, B-9000 Gent, Belgium and Environment Agency, Evenlode House, Howbery Park, Wallingford, Oxon OX10 ...;Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure links 653, B-9000 Gent, Belgium

  • Venue:
  • International Journal of Approximate Reasoning
  • Year:
  • 2007

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Abstract

Fuzzy ordered classifiers were used to assign fuzzy labels to river sites expressing their suitability as a habitat for a certain macroinvertebrate taxon, given up to three abiotic properties of the considered river site. The models were built using expert knowledge and evaluated on data collected in the Province of Overijssel in the Netherlands. Apart from a performance measure for crisp classifiers common in the aquatic ecology domain, the percentage of correctly classified instances (% CCI), two performance measures for fuzzy (ordered) classifiers are introduced in this paper: the percentage of correctly fuzzy classified instances (% CFCI) and the average deviation (AD). Furthermore, results of an interpretability-preserving genetic optimization of the linguistic terms, applying once binary encoding and once real encoding, are presented.