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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2018-01-01
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Series: | ITM Web of Conferences |
Online Access: | https://doi.org/10.1051/itmconf/20181804001 |
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doaj-2ca0d5e28acf4dbd922872f06fcb14be2021-02-02T08:43:56ZengEDP SciencesITM Web of Conferences2271-20972018-01-01180400110.1051/itmconf/20181804001itmconf_ics2018_04001Data classification based on the hybrid intellectual technologyDemidova LiliyaEgin MaksimIn 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.https://doi.org/10.1051/itmconf/20181804001 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Demidova Liliya Egin Maksim |
spellingShingle |
Demidova Liliya Egin Maksim Data classification based on the hybrid intellectual technology ITM Web of Conferences |
author_facet |
Demidova Liliya Egin Maksim |
author_sort |
Demidova Liliya |
title |
Data classification based on the hybrid intellectual technology |
title_short |
Data classification based on the hybrid intellectual technology |
title_full |
Data classification based on the hybrid intellectual technology |
title_fullStr |
Data classification based on the hybrid intellectual technology |
title_full_unstemmed |
Data classification based on the hybrid intellectual technology |
title_sort |
data classification based on the hybrid intellectual technology |
publisher |
EDP Sciences |
series |
ITM Web of Conferences |
issn |
2271-2097 |
publishDate |
2018-01-01 |
description |
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. |
url |
https://doi.org/10.1051/itmconf/20181804001 |
work_keys_str_mv |
AT demidovaliliya dataclassificationbasedonthehybridintellectualtechnology AT eginmaksim dataclassificationbasedonthehybridintellectualtechnology |
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