DocumentCode :
2556289
Title :
Research on the classifier with the tree frame based on multiple attractor cellular automaton
Author :
Fang Min ; Zhang Xiao Song ; Niu WenKe
Author_Institution :
Inst. of Comput. Sci., Xidian Univ., Xi´an, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
1079
Lastpage :
1083
Abstract :
The partition of a pattern space as the view of a cell space is a uniform partition, it is difficult to adapt to the needs of spatial non-uniform partition. In this paper, a cellular automaton classifier with a tree structure is constructed by combing with the CART algorithm. The construction method of the characteristic matrix of the multiple attractor cellular automata is studied based on the particle swarm optimization method, and this method can build the nodes of the multiple attractor cellular automata. This kind of classifier can solve the non-uniform partition problem and obtain a good classification performance while using a pseudo-exhaustive field with less bits. The experiment results show that our algorithm is more accurate than those obtained through the multiple attractor cellular automata.
Keywords :
cellular automata; decision trees; matrix algebra; particle swarm optimisation; pattern classification; tree data structures; CART algorithm; cell space; characteristic matrix; multiattractor cellular automata; particle swarm optimization; pattern classification; pattern space; pseudoexhaustive field; spatial nonuniform partition problem; tree structure; Automata; Classification algorithms; Particle swarm optimization; Partitioning algorithms; Polynomials; Testing; Training; CART Algorithm; Multiple Attractor Cellular Automata; Pattern Classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234512
Filename :
6234512
Link To Document :
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