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...

Full description

Bibliographic Details
Main Authors: Demidova Liliya, Egin Maksim
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:ITM Web of Conferences
Online Access:https://doi.org/10.1051/itmconf/20181804001
id doaj-2ca0d5e28acf4dbd922872f06fcb14be
record_format Article
spelling 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
_version_ 1724296551627489280