Fuzzy Classification with Multi-objective Evolutionary Algorithms

被引：0

作者：

Jimenez, Fernando ^{[1
]}

Sanchez, Gracia ^{[1
]}

Sanchez, Jose F. ^{[1
]}

Alcaraz, Jose M. ^{[1
]}

机构：

[1] Fac Informat Campus Espinardo, Murcia 30071, Spain

来源：

HYBRID ARTIFICIAL INTELLIGENCE SYSTEMS | 2008年 / 5271卷

关键词：

Multi-objective Evolutionary algorithms; Fuzzy classification;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work we propose, on the one hand, a multi-objective constrained optimization model to obtain fuzzy models for classification considering criteria of accuracy and interpretability. On the other hand, we propose an evolutionary multi-objective approach for fuzzy classification from data with real and discrete attributes. The multi-objective evolutionary approach has been evaluated by means of three different evolutionary schemes: Preselection with niches, NSGA-II and ENORA. The results have been compared in terms of effectiveness by means of statistical techniques using the well-known standard Iris data set.

引用

页码：730 / 738

页数：9

共 50 条

[1] Multi-objective evolutionary algorithms for fuzzy classification in survival prediction
Jimenez, Fernando
Sanchez, Gracia
Juarez, Jose M.
[J]. ARTIFICIAL INTELLIGENCE IN MEDICINE, 2014, 60 (03) : 197 - 219
[2] On the use of multi-objective evolutionary algorithms for the induction of fuzzy classification rule systems
Setzkorn, C
Paton, RC
[J]. BIOSYSTEMS, 2005, 81 (02) : 101 - 112
[3] Multi-objective evolutionary algorithms based fuzzy optimization
Sánchez, G
Jiménez, F
Gómez-Skarmeta, AF
[J]. 2003 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-5, CONFERENCE PROCEEDINGS, 2003, : 1 - 7
[4] Nonlinear optimization with fuzzy constraints by multi-objective evolutionary algorithms
Jiménez, F
Sánchez, G
Cadenas, JM
Gómez-Skarmeta, AF
Verdegay, JL
[J]. Computational Intelligence, Theory and Applications, 2005, : 713 - 722
[5] Fuzzy optimization with multi-objective evolutionary algorithms: a case study
Sanchez, G.
Jimenez, F.
Vasant, P.
[J]. 2007 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN MULTI-CRITERIA DECISION MAKING, 2007, : 58 - +
[6] Evolutionary multi-objective optimization algorithms for fuzzy portfolio selection
Saborido, Ruben
Ruiz, Ana B.
Bermudez, Jose D.
Vercher, Enriqueta
Luque, Mariano
[J]. APPLIED SOFT COMPUTING, 2016, 39 : 48 - 63
[7] Mining classification rules using evolutionary multi-objective algorithms
Kshetrapalapuram, KK
Kirley, M
[J]. KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 3, PROCEEDINGS, 2005, 3683 : 959 - 965
[8] A multi-objective evolutionary algorithms with group fuzzy decision making method
Qin, Yongfa
Gong, Qingsong
[J]. PROGRESS IN INTELLIGENCE COMPUTATION AND APPLICATIONS, PROCEEDINGS, 2007, : 132 - 137
[9] A fuzzy based approach for fitness approximation in multi-objective evolutionary algorithms
Pourbahman, Zahra
Hamzeh, Ali
[J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2015, 29 (05) : 2111 - 2131
[10] MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS FOR FILTER BASED FEATURE SELECTION IN CLASSIFICATION
Xue, Bing
Cervante, Liam
Shang, Lin
Browne, Will N.
Zhang, Mengjie
[J]. INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 2013, 22 (04)

← 1 2 3 4 5 →