Publication:
Enhancing the efficiency of the interval-valued fuzzy rule-based classifier with tuning and rule selection

Consultable a partir de

2021-06-05

Date

2020

Director

Publisher

Springer
Acceso abierto / Sarbide irekia
Contribución a congreso / Biltzarrerako ekarpena
Versión aceptada / Onetsi den bertsioa

Project identifier

ES/1PE/TIN2016-77356-P

Abstract

Interval-Valued fuzzy rule-based classifier with TUning and Rule Selection, IVTURS, is a state-of-the-art fuzzy classifier. One of the key point of this method is the usage of interval-valued restricted equivalence functions because their parametrization allows one to tune them to each problem, which leads to obtaining accurate results. However, they require the application of the exponentiation several times to obtain a result, which is a time demanding operation implying an extra charge to the computational burden of the method. In this contribution, we propose to reduce the number of exponentiation operations executed by the system, so that the efficiency of the method is enhanced with no alteration of the obtained results. Moreover, the new approach also allows for a reduction on the search space of the evolutionary method carried out in IVTURS. Consequently, we also propose four different approaches to take advantage of this reduction on the search space to study if it can imply an enhancement of the accuracy of the classifier. The experimental results prove: 1) the enhancement of the efficiency of IVTURS and 2) the accuracy of IVTURS is competitive versus that of the approaches using the reduced search space.

Keywords

Interval-valued fuzzy rule-based classification systems, Interval-valued fuzzy sets, Interval type-2 fuzzy sets, Evolutionary fuzzy systems

Department

Institute of Smart Cities - ISC

Faculty/School

Degree

Doctorate program

Editor version

Funding entities

This work was supported in part by the Spanish Ministry of Science and Technology (project TIN2016-77356-P (AEI/FEDER, UE)) and the Public University of Navarre under the project PJUPNA1926.

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