Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/7607
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ng, Sai-Cheong | en_US |
dc.contributor.author | Prof. LEUNG Kwong Sak | en_US |
dc.date.accessioned | 2023-03-27T04:09:37Z | - |
dc.date.available | 2023-03-27T04:09:37Z | - |
dc.date.issued | 2005 | - |
dc.identifier.citation | Lecture Notes in Computer Science, 2005, Vol. 3578, pp. 264 - 271 | en_US |
dc.identifier.issn | 03029743 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11861/7607 | - |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer Verlag | en_US |
dc.relation.ispartof | Lecture Notes in Computer Science | en_US |
dc.title | Induction of linear decision trees with real-coded genetic algorithms and k-D trees | en_US |
dc.type | Peer Reviewed Journal Article | en_US |
dc.identifier.doi | 10.1007/11508069_35 | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Applied Data Science | - |
Appears in Collections: | Applied Data Science - Publication |
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