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License Agreement on scientific materials use.
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SOLUTION OF AUTOMATIC SELECTION OF ALGORITHM FRIS-CLUSTER PARAMETER R*
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Aleksandr Olegovich Zyryanov
Novosibirsk State University
Evgenii Nikolaevich Pavlovskii
Novosibirsk State University
Vladimir Vladimirovich Dyubanov
Novosibirsk
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Submitted:
July 10, 2014
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Abstract.
The work is devoted to the clustering algorithm FRiS-Cluster, the weak point of which is the parameter r*. This parameter must be specified manually, thus the correctness of choice can be judged only at the end of the algorithm. The article explores the dependence of the quality of clustering task solution on the value of r*. The heuristics for determining the obviously poor quality of clustering before the end of the algorithm working is formulated. On the basis of the derived heuristics an algorithm for automatic selecting the parameter r* is proposed.
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Key words and phrases:
кластеризация
кластерный анализ
таксономия
FRiS-методология
столп
когнитивный анализ данных
виртуальный противник
расстояние до виртуального противника
clustering
cluster analysis
taxonomy
FRiS-methodology
pillar
cognitive analysis of data
virtual opponent
distance to virtual opponent
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Open
the whole article in PDF format. Free PDF-files viewer can be downloaded here.
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References:
- Загоруйко Н. Г. Когнитивный анализ данных. Новосибирск: Гео, 2013.
- Borisova I. A., Dyubanov V. V., Kutnenko O. A., Zagoruiko N. G. Use of the FRiS-Function for Taxonomy, Attribute Selection and Decision Rule Construction // Lecture Notes in Artificial Intelligence. 2011. V. 6581. P. 256-270.
- Zagoruiko N. G., Borisova I. A., Dyubanov V. V., Kutnenko O. A. A Quantitative Measure of Compactness and Similarity in a Competitive Space // Journal of Applied and Industrial Mathematics. 2011. Vol. 5. № 1. P. 144-154. DOI: 10.1134/S1990478911010157.
- Zagoruiko N. G., Borisova I. A., Dyubanov V. V., Kutnenko O. A. Methods of Recognition Based on the Function of Rival Similarity // Pattern Recognition and Image Analysis. 2008. Vol. 18. № 1. P. 1-6. DOI: 10.1007/s11493-008-1001-8.
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