ITM Web Conf.
Volume 18, 20187th Seminar on Industrial Control Systems: Analysis, Modeling and Computing (ICS 2018)
|Number of page(s)||5|
|Published online||09 April 2018|
Data classification based on the hybrid intellectual technology
Ryazan State Radio Engineering University, 390005 Ryazan, Russia
* Corresponding author: firstname.lastname@example.org
In this paper the data classification technique, implying the consistent application of the SVM and Parzen classifiers, has been suggested. The Parser classifier applies to data which can be both correctly and erroneously classified using the SVM classifier, and are located in the experimentally defined subareas near the hyperplane which separates the classes. A herewith, the SVM classifier is used with the default parameters values, and the optimal parameters values of the Parser classifier are determined using the genetic algorithm. The experimental results confirming the effectiveness of the proposed hybrid intellectual data classification technology have been presented.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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