Data classification based on the hybrid intellectual technology

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 def...

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Bibliographic Details
Published in:ITM web of conferences 2018, Vol.18, p.4001
Main Authors: Demidova, Liliya, Egin, Maksim
Format: Article
Language:English
Subjects:
Classification
Classifiers
Genetic algorithms
Parameters
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Summary: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.
ISSN:2271-2097
2431-7578
2271-2097
DOI:10.1051/itmconf/20181804001