DocumentCode :
2437849
Title :
Searching the forest: using decision trees as building blocks for evolutionary search in classification databases
Author :
Rouwhorst, SE ; Engelbrecht, AP
Author_Institution :
Dept. of Inf. & Math., Vrije Univ., Amsterdam, Netherlands
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
633
Abstract :
A new evolutionary search algorithm, called BGP (Building-block approach to Genetic Programming), to be used for classification tasks in data mining, is introduced. It is different from existing evolutionary techniques in that it does not use indirect representations of a solution, such as bit strings or grammars. The algorithm uses decision trees of various sizes as individuals in the populations and operators, e.g. crossover, are performed directly on the trees. When compared to the C4.5 and CN2 induction algorithms on a benchmark set of problems, BGP shows very good results
Keywords :
data mining; decision trees; evolutionary computation; mathematical operators; pattern classification; search problems; BGP algorithm; C4.5 algorithm; CN2 algorithm; building blocks; classification databases; data mining; decision trees; evolutionary search algorithm; genetic programming; induction algorithms; operators; Artificial intelligence; Classification tree analysis; Data analysis; Data mining; Databases; Decision trees; Genetic programming; Informatics; Mathematics; Pattern analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
Type :
conf
DOI :
10.1109/CEC.2000.870357
Filename :
870357
Link To Document :
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