Guarantied Single Disk Access for Very Large Database Files
Dejan Simić, Dušan Starčević, Emil Jovanov (1997)
The Yugoslav Journal of Operations Research
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Dejan Simić, Dušan Starčević, Emil Jovanov (1997)
The Yugoslav Journal of Operations Research
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Miroslav Sabo (2014)
Kybernetika
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Consensus clustering algorithms are used to improve properties of traditional clustering methods, especially their accuracy and robustness. In this article, we introduce our approach that is based on a refinement of the set of initial partitions and uses differential evolution algorithm in order to find the most valid solution. Properties of the algorithm are demonstrated on four benchmark datasets.
Osvaldo Silva, Helena Bacelar-Nicolau, Fernando C. Nicolau (2012)
Biometrical Letters
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The discovery of knowledge in the case of Hierarchical Cluster Analysis (HCA) depends on many factors, such as the clustering algorithms applied and the strategies developed in the initial stage of Cluster Analysis. We present a global approach for evaluating the quality of clustering results and making a comparison among different clustering algorithms using the relevant information available (e.g. the stability, isolation and homogeneity of the clusters). In addition, we present a...
Kristína Machová, Miroslav Puszta, František Barčák, Peter Bednár (2006)
Computer Science and Information Systems
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Przemysław Grudziński, Marek Wojciechowski (2009)
Control and Cybernetics
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Zoltán Mann, András Orbán, Viktor Farkas (2007)
International Journal of Applied Mathematics and Computer Science
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In recent years, several heuristics have been proposed for the hardware/software partitioning problem. One of the most promising directions is the adaptation of the Kernighan-Lin algorithm. The Kernighan-Lin heuristic was originally developed for circuit partitioning, but it has been adapted to other domains as well. Moreover, numerous improvements have been suggested so that now several variants of the original algorithm exist. The aim of this paper is to systematically evaluate the...
Milan M. Milosavljević, Milan Ž. Marković (1999)
The Yugoslav Journal of Operations Research
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Ireneusz Czarnowski, Piotr Jędrzejowicz (2011)
International Journal of Applied Mathematics and Computer Science
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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...
Vladan Devedžić, Dušan Velašević, Zoran Božović (1993)
The Yugoslav Journal of Operations Research
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Jerzy Stefanowski, Dawid Weiss (2007)
Control and Cybernetics
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Rafał Biedrzycki, Jarosław Arabas (2012)
International Journal of Applied Mathematics and Computer Science
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This paper presents an application of methods from the machine learning domain to solving the task of DNA sequence recognition. We present an algorithm that learns to recognize groups of DNA sequences sharing common features such as sequence functionality. We demonstrate application of the algorithm to find splice sites, i.e., to properly detect donor and acceptor sequences. We compare the results with those of reference methods that have been designed and tuned to detect splice sites....
Nenad Mladenović, José A. Moreno, J. Marcos Moreno-Vega (1996)
The Yugoslav Journal of Operations Research
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