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A Construction Method of Fuzzy Classifiers Using Confidence-weighted Learning
2013
Procedia Computer Science
Incremental algorithms for fuzzy classifiers are studied in this paper. It is assumed that not all training patterns are given a priori for training classifiers, but are gradually made available over time. It is also assumed that the previously available training patterns can not be used afterwards. Thus, fuzzy classifiers should be modified by updating already constructed classifiers using the available training patterns. In this paper, a confidence-weighted (CW) learning algorithm is applied
doi:10.1016/j.procs.2013.09.124
fatcat:4a4hsa542bemromvsav23wbyom