Title :
Primal-dual version spaces
Author :
Hong, Tzung-Pei ; Tseng, Shian-Shyong
Author_Institution :
Dept. of Inf. Manage., Kaohsiung Polytech. Inst., Taiwan
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-3280-6
DOI :
10.1109/ICSMC.1996.565476