dc.contributor.author | Sanz, José Antonio | |
dc.contributor.author | Fernández, Alberto | |
dc.contributor.author | Bustince, Humberto | |
dc.contributor.author | Herrera Triguero, Francisco | |
dc.date.accessioned | 2020-12-16T08:12:28Z | |
dc.date.available | 2020-12-16T08:12:28Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | J. A. Sanz, A. Fernández, H. Bustince and F. Herrera, "IVTURS: A Linguistic Fuzzy Rule-Based Classification System Based On a New Interval-Valued Fuzzy Reasoning Method With Tuning and Rule Selection," in IEEE Transactions on Fuzzy Systems, vol. 21, no. 3, pp. 399-411, June 2013, [doi: 10.1109/TFUZZ.2013.2243153] | es_ES |
dc.identifier.uri | http://hdl.handle.net/10481/64936 | |
dc.description.abstract | Interval-valued fuzzy sets have been shown to be
a useful tool for dealing with the ignorance related to the
definition of the linguistic labels. Specifically, they have been
successfully applied to solve classification problems, performing
simple modifications on the fuzzy reasoning method to work with
this representation and making the classification based on a single
number.
In this paper we present IVTURS, a new linguistic fuzzy rulebased classification method based on a new completely intervalvalued fuzzy reasoning method. This inference process uses
interval-valued restricted equivalence functions to increase the
relevance of the rules in which the equivalence of the interval
membership degrees of the patterns and the ideal membership
degrees is greater, which is a desirable behaviour. Furthermore,
their parametrized construction allows the computation of the
optimal function for each variable to be performed, which
could involve a potential improvement in the system’s behaviour.
Additionally, we combine this tuning of the equivalence with rule
selection in order to decrease the complexity of the system. In
this paper we name our method IVTURS-FARC, since we use
the FARC-HD method [1] to accomplish the fuzzy rule learning
process.
The experimental study is developed in three steps in order to
ascertain the quality of our new proposal. First, we determine
both the essential role that interval-valued fuzzy sets play in
the method and the need for the rule selection process. Next, we
show the improvements achieved by IVTURS-FARC with respect
to the tuning of the degree of ignorance when it is applied in
both an isolated way and when combined with the tuning of the
equivalence. Finally, the significance of IVTURS-FARC is further
depicted by means of a comparison by which it is proved to
outperform the results of FARC-HD and FURIA [2], which are
two high performing fuzzy classification algorithms. | es_ES |
dc.description.sponsorship | Spanish Government
TIN2011-28488
TIN2010-15055 | es_ES |
dc.description.sponsorship | Andalusian Research
P10-TIC-6858
P11-TIC-7765 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | es_ES |
dc.rights | Atribución 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Linguistic Fuzzy Rule-Based Classification Systems | es_ES |
dc.subject | Interval-valued fuzzy set | es_ES |
dc.subject | Fuzzy Reasoning Method | es_ES |
dc.subject | Interval-Valued Restricted Equivalence Functions | es_ES |
dc.subject | Tuning | es_ES |
dc.subject | Rule Selection | es_ES |
dc.title | IVTURS: a linguistic fuzzy rule-based classification system based on a new Interval-Valued fuzzy reasoning method with TUning and Rule Selection | es_ES |
dc.type | journal article | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.1109/TFUZZ.2013.2243153 | |