Intelligence in manufacturing systems: the pattern recognition perspective
Marek Zaremba (2010)
Control and Cybernetics
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Marek Zaremba (2010)
Control and Cybernetics
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Koychev, Ivan (2007)
Serdica Journal of Computing
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This paper addresses the task of learning classifiers from streams of labelled data. In this case we can face the problem that the underlying concepts can change over time. The paper studies two mechanisms developed for dealing with changing concepts. Both are based on the time window idea. The first one forgets gradually, by assigning to the examples weight that gradually decreases over time. The second one uses a statistical test to detect changes in concept and then optimizes the...
Lin, Chia-Hung, Chen, Jian-Liung, Gaing, Zwe-Lee (2010)
Mathematical Problems in Engineering
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Francesc J. Ferri (1998)
Kybernetika
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Prototype Selection (PS) techniques have traditionally been applied prior to Nearest Neighbour (NN) classification rules both to improve its accuracy (editing) and to alleviate its computational burden (condensing). Methods based on selecting/discarding prototypes and methods based on adapting prototypes have been separately introduced to deal with this problem. Different approaches to this problem are considered in this paper and their main advantages and drawbacks are pointed out along...
Fisher, A.C., Lake, S.P., Cunningham, I.P., Chandna, A. (2010)
Computational & Mathematical Methods in Medicine
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Zhao Zhang, Ning Ye (2010)
Computer Science and Information Systems
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Liming Yuan, Jiafeng Liu, Xianglong Tang (2014)
International Journal of Applied Mathematics and Computer Science
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Jasmina Novaković, Perica Strbac, Dusan Bulatović (2011)
The Yugoslav Journal of Operations Research
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Michał Muszyński, Stanisław Osowski (2014)
International Journal of Applied Mathematics and Computer Science
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Roman Świniarski (2001)
International Journal of Applied Mathematics and Computer Science
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The paper presents an application of rough sets and statistical methods to feature reduction and pattern recognition. The presented description of rough sets theory emphasizes the role of rough sets reducts in feature selection and data reduction in pattern recognition. The overview of methods of feature selection emphasizes feature selection criteria, including rough set-based methods. The paper also contains a description of the algorithm for feature selection and reduction based on...