DocumentCode :
1879329
Title :
A hybrid particle swarm/ant colony algorithm for the classification of hierarchical biological data
Author :
Holden, Nicholas ; Freitas, Alex A.
Author_Institution :
Comput. Lab., Kent Univ., Canterbury, UK
fYear :
2005
fDate :
8-10 June 2005
Firstpage :
100
Lastpage :
107
Abstract :
This paper proposes a hybrid PSO/ACO algorithm for hierarchical classification, where the classes to be predicted are arranged in a tree-like hierarchy. The performance of the algorithm is evaluated on a challenging biological data set, involving the hierarchical functional classification of enzymes. The proposed algorithm is compared with an existing PSO for classification, which was also adapted for hierarchical classification.
Keywords :
biology computing; data mining; particle swarm optimisation; pattern classification; ant colony algorithm; enzymes classification; hierarchical biological data classification; particle swarm optimization; tree-like hierarchy; Amino acids; Biochemistry; Biology computing; Chemicals; Classification algorithms; Classification tree analysis; Databases; Laboratories; Particle swarm optimization; Proteins;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Swarm Intelligence Symposium, 2005. SIS 2005. Proceedings 2005 IEEE
Print_ISBN :
0-7803-8916-6
Type :
conf
DOI :
10.1109/SIS.2005.1501608
Filename :
1501608
Link To Document :
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