DocumentCode :
2415527
Title :
Aggregation of Fuzzy Classifiers Using Coupled Map Lattices
Author :
Gomez, Jónatan ; León, Elizabeth
Author_Institution :
Univ. Nacional de Colombia, Manizales
fYear :
0
fDate :
0-0 0
Firstpage :
344
Lastpage :
350
Abstract :
This paper proposes a technique for aggregating a group of fuzzy classifiers using a coupled map lattice. First a the training data set is divided into several disjoint groups. Each group is used for training a classifier using a fuzzy classification technique. Then, each fuzzy classifier is associated to one site in a coupled map lattice. In order to predict the class of a given data sample, the sample is presented to each fuzzy classifier and the prediction is evolved using the dynamics properties of the coupled map lattice. The final prediction is the fuzzy voting of the classifiers after evolving them. The proposed approach is tested with several toy and real data sets in order to determine its performance.
Keywords :
fuzzy logic; fuzzy set theory; group theory; learning (artificial intelligence); pattern classification; coupled map lattice; data set training; disjoint group; dynamics property; fuzzy classification aggregation; fuzzy logic; fuzzy voting; Chaos; Data mining; Fuzzy sets; Lattices; Machine learning; Performance analysis; Supervised learning; Testing; Training data; Voting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2006 IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9488-7
Type :
conf
DOI :
10.1109/FUZZY.2006.1681735
Filename :
1681735
Link To Document :
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