Title :
Handling High-Dimensional Regression Problems by Means of an Efficient Multi-Objective Evolutionary Algorithm
Author :
Gacto, María José ; Alcala, Rafael ; Herrera, Francisco
Author_Institution :
Dept. Comput. Sci., Univ. of Jaen, Jaen, Spain
fDate :
Nov. 30 2009-Dec. 2 2009
Abstract :
Linguistic fuzzy modeling in high dimensional regression problems is a challenging topic since conventional linguistic fuzzy rule-based systems suffer from exponential rule explosion when the number of variables and/or data examples becomes high. A good way to face this problem is by searching for a good and simple global structure within the same process, in order to consider the relationships among the different components defining the final linguistic model. In this contribution, we propose an effective multi-objective evolutionary algorithm that based on the data base learning a priori (involved variables, granularities and slight uniform displacements of the fuzzy partitions) allows a fast derivation of simple and quite accurate linguistic models, making use of some effective mechanisms in order to ensure a fast convergence. The good results obtained in several large-scale regression problems demonstrate the effectiveness of the proposed approach.
Keywords :
computational complexity; computational linguistics; evolutionary computation; fuzzy reasoning; knowledge based systems; regression analysis; complexity reduction; data base learning a priori; high dimensional regression problem; linguistic fuzzy modeling; linguistic fuzzy rule based system; multi-objective evolutionary algorithm; multi-objective genetic fuzzy systems; Application software; Artificial intelligence; Computer science; Convergence; Evolutionary computation; Explosions; Fuzzy systems; Intelligent systems; Knowledge based systems; Large-scale systems; High-dimensional regression problems; complexity reduction; linguistic fuzzy modeling; multi-objective genetic fuzzy systems;
Conference_Titel :
Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on
Conference_Location :
Pisa
Print_ISBN :
978-1-4244-4735-0
Electronic_ISBN :
978-0-7695-3872-3
DOI :
10.1109/ISDA.2009.214