Czasopismo
Tytuł artykułu
Warianty tytułu
Języki publikacji
Abstrakty
The problem considered concerns data reduction for machine learning. Data reduction aims at deciding which features and instances from the training set should be retained for further use during the learning process. Data reduction results in increased capabilities and generalization properties of the learning model and a shorter time of the learning process. It can also help in scaling up to large data sources. The paper proposes an agent-based data reduction approach with the learning process executed by a team of agents (A-Team). Several A-Team architectures with agents executing the simulated annealing and tabu search procedures are proposed and investigated. The paper includes a detailed description of the proposed approach and discusses the results of a validating experiment.
Słowa kluczowe
Wydawca
Rocznik
Tom
Numer
Strony
57-68
Opis fizyczny
Daty
wydano
2011
otrzymano
2010-04-13
poprawiono
2010-11-15
Twórcy
autor
- Department of Information Systems, Gdynia Maritime University, Morska 83, 81-225 Gdynia, Poland
autor
- Department of Information Systems, Gdynia Maritime University, Morska 83, 81-225 Gdynia, Poland
Bibliografia
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Typ dokumentu
Bibliografia
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Identyfikator YADDA
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