DocumentCode :
305413
Title :
Primal-dual version spaces
Author :
Hong, Tzung-Pei ; Tseng, Shian-Shyong
Author_Institution :
Dept. of Inf. Manage., Kaohsiung Polytech. Inst., Taiwan
Volume :
3
fYear :
1996
fDate :
14-17 Oct 1996
Firstpage :
2145
Abstract :
Several learning strategies, based on the version space learning strategy, have been proposed to incrementally learn disjunctive concepts from examples. All of them must however store past training instances for the learning process to be successful. If the amount of training data is large, it then causes a heavy load. We propose a new learning strategy, the “primal-dual version spaces” learning strategy, which can incrementally learn disjunctive concepts well without keeping track of the past training instances at all
Keywords :
learning (artificial intelligence); disjunctive concepts; incremental learning; learning strategy; primal-dual version spaces; Convergence; Information management; Information science; Intrusion detection; Law; Learning systems; Legal factors; Management training; Testing; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Conference_Location :
Beijing
ISSN :
1062-922X
Print_ISBN :
0-7803-3280-6
Type :
conf
DOI :
10.1109/ICSMC.1996.565476
Filename :
565476
Link To Document :
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