Name
Title | ||
|---|---|---|
A Study On The Use Of Multiobjective Genetic Algorithms For Classifier Selection In Furia-Based Fuzzy Multiclassifiers |
Abstract | ||
|---|---|---|
In a preceding contribution, we conducted a study considering a fuzzy multiclassifier system (MCS) design framework based on Fuzzy Unordered Rule Induction Algorithm (FURIA). It served as the fuzzy rule classification learning algorithm to derive the component classifiers considering bagging and feature selection. In this work, we integrate this approach under the overproduce-and-choose strategy. A state-of-the-art evolutionary multiobjective algorithm, namely NSGA-II, is used to provide a component classifier selection and improve FURIA-based fuzzy MCS. We propose five different fitness functions based on three different optimization criteria, accuracy, complexity, and diversity. Twenty UCI high dimensional datasets were considered in order to conduct the experiments. A combination between accuracy and diversity criteria provided very promising results, becoming competitive with classical MCS learning methods. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1080/18756891.2012.685272 | INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS |
Keywords | Field | DocType |
Fuzzy rule-based multiclassification systems, bagging, FURIA, genetic selection of individual classifiers, diversity measures, evolutionary multiobjective optimization, NSGA-II | Design framework,Feature selection,Fuzzy logic,Rule induction,Artificial intelligence,Classifier (linguistics),Mathematics,Genetic algorithm,Machine learning,Fuzzy rule | Journal |
Volume | Issue | ISSN |
5 | 2 | 1875-6891 |
Citations | PageRank | References |
15 | 0.54 | 41 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Krzysztof Trawiński | 1 | 247 | 16.06 |
| Oscar Cordón | 2 | 1572 | 100.75 |
| Arnaud Quirin | 3 | 168 | 13.68 |