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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Liming Yuan, Jiafeng Liu, Xianglong Tang (2014)
International Journal of Applied Mathematics and Computer Science
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Karol Grudziński (2010)
Control and Cybernetics
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Jasmina Novaković, Perica Strbac, Dusan Bulatović (2011)
The Yugoslav Journal of Operations Research
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Michał Woźniak, Bartosz Krawczyk (2012)
International Journal of Applied Mathematics and Computer Science
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This paper presents a significant modification to the AdaSS (Adaptive Splitting and Selection) algorithm, which was developed several years ago. The method is based on the simultaneous partitioning of the feature space and an assignment of a compound classifier to each of the subsets. The original version of the algorithm uses a classifier committee and a majority voting rule to arrive at a decision. The proposed modification replaces the fairly simple fusion method with a combined classifier,...
Lin, Chia-Hung, Chen, Jian-Liung, Gaing, Zwe-Lee (2010)
Mathematical Problems in Engineering
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Jan Rybka, Artur Janicki (2013)
International Journal of Applied Mathematics and Computer Science
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This paper describes a study of emotion recognition based on speech analysis. The introduction to the theory contains a review of emotion inventories used in various studies of emotion recognition as well as the speech corpora applied, methods of speech parametrization, and the most commonly employed classification algorithms. In the current study the EMO-DB speech corpus and three selected classifiers, the k-Nearest Neighbor (k-NN), the Artificial Neural Network (ANN) and Support Vector...
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...
Zhao Zhang, Ning Ye (2010)
Computer Science and Information Systems
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Rajeev Kumar, Peter I Rockett (1998)
Kybernetika
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In this paper we present a novel approach to decomposing high dimensional spaces using a multiobjective genetic algorithm for identifying (near-)optimal subspaces for hierarchical classification. This strategy of pre-processing the data and explicitly optimising the partitions for subsequent mapping onto a hierarchical classifier is found to both reduce the learning complexity and the classification time with no degradation in overall classification error rate. Results of partitioning...
Michał Muszyński, Stanisław Osowski (2014)
International Journal of Applied Mathematics and Computer Science
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Krzysztof Siwek, Stanisław Osowski (2016)
International Journal of Applied Mathematics and Computer Science
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The paper discusses methods of data mining for prediction of air pollution. Two tasks in such a problem are important: generation and selection of the prognostic features, and the final prognostic system of the pollution for the next day. An advanced set of features, created on the basis of the atmospheric parameters, is proposed. This set is subject to analysis and selection of the most important features from the prediction point of view. Two methods of feature selection are compared....