The inductive model of the objective clustering of objects based on the k-means algorithm clustering is presented in the paper. The algorithm for division of initial data into two equal power subsets is proposed and practically implemented. The difference between the mass centres of the appropriate clusters in different clustering is proposed to use as an external balance criterion. Approbation of the proposed model operation was carried out using the data “Compound” and “Aggregation” of the database of the Computing School in the Eastern Finland University. The researches on the estimation of the model stability to a noise component using the data “Seeds” are presented in the paper. The algorithms k-means, c-means, inductive k-means and agglomerative hierarchical algorithm were used to compare the results of the experiment. The ways of further improvement of the proposed model in order to increase the objectivity of investigated data clustering were defined by the results of the simulation.
Науковий журнал «Радіоелектроніка, інформатика, управління»
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Babichev, S. A.; Jan Evangelista Purkyne University in Usti nad
Labem, Czech Republic Lytvynenko, V. I.; Kherson National Technical University, Kherson, Ukraine Taif, M. A.; Kherson National Technical University, Kherson, Ukraine |
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The inductive model of the objective clustering of objects based on the k-means algorithm clustering is presented in the paper. The algorithm for division of initial data into two equal power subsets is proposed and practically implemented. The difference between the mass centres of the appropriate clusters in different clustering is proposed to use as an external balance criterion. Approbation of the proposed model operation was carried out using the data “Compound” and “Aggregation” of the database of the Computing School in the Eastern Finland University. The researches on the estimation of the model stability to a noise component using the data “Seeds” are presented in the paper. The algorithms k-means, c-means, inductive k-means and agglomerative hierarchical algorithm were used to compare the results of the experiment. The ways of further improvement of the proposed model in order to increase the objectivity of investigated data clustering were defined by the results of the simulation. |
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Zaporizhzhya National Technical University 2017-01-20 00:00:00 |
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application/pdf http://ric.zntu.edu.ua/article/view/90346 |
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Radio Electronics, Computer Science, Control; No 4 (2016): Radio Electronics, Computer Science, Control |
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Copyright (c) 2017 S. A. Babichev, V. I. Lytvynenko, M. A. Taif |
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