Metadata language
Evolutionary algorithm to derive classification rules from sets of example
Subtitle:Raport Badawczy = Research Report ; RB/23/2001
Creator: Publisher:Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences
Place of publishing: Date issued/created: Description:19 pages ; 21 cm ; Bibliography p. 18
Subject and Keywords:Genetic algorithm ; Algorytm genetyczny ; Algorytm ewolucyjny ; Evolutionary algorithm ; Learning from examoples ; Heuristic operators ; Adaptacyjny algorytm ewolucyjny ; Adaptive evolutionary algorithm ; Operatory heurystyczne ; Uczenie się na przykładach
Abstract:The article proposes a method to derive classification rules that correctly describe all the examples belonging to a class and do not describe all the examples not belonging to this class. The method bases on an evolutionary algorithm with dedicated to that problem specialized operators and a method of valuing their behavior. The new concept of the proposed method is that every solution obtained from the algorithm (every member of the population in the evolutionary algorithm) contains rules which describe all classes of the training data. So it is a complete solution that covers all the examples presented to the algorithm.
Relation:Raport Badawczy = Research Report
Resource type: Detailed Resource Type: Source: Language: Language of abstract: Rights:Creative Commons Attribution BY 4.0 license
Terms of use:Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -
Digitizing institution:Systems Research Institute of the Polish Academy of Sciences
Original in:Library of Systems Research Institute PAS
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