Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7607
Title: Induction of linear decision trees with real-coded genetic algorithms and k-D trees
Authors: Ng, Sai-Cheong 
Prof. LEUNG Kwong Sak 
Issue Date: 2005
Publisher: Springer Verlag
Source: Lecture Notes in Computer Science, 2005, Vol. 3578, pp. 264 - 271
Journal: Lecture Notes in Computer Science 
Abstract: Although genetic algorithm-based decision tree algorithms are applied successfully in various classification tasks, their execution times are quite long on large datasets. A novel decision tree algorithm, called Real-Coded Genetic Algorithm-based Linear Decision Tree Algorithm with k-D Trees (RCGA-based LDT with kDT), is proposed. In the proposed algorithm, a k-D tree is built when a new node of a linear decision tree is created. The use of k-D trees speeds up the construction of linear decision trees without sacrificing the quality of the constructed decision trees. © Springer-Verlag Berlin Heidelberg 2005.
Type: Peer Reviewed Journal Article
URI: http://hdl.handle.net/20.500.11861/7607
ISSN: 03029743
DOI: 10.1007/11508069_35
Appears in Collections:Applied Data Science - Publication

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