Automatic Neonatal Sleep EEG Recognition with Social Impact based Feature Selection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00194837" target="_blank" >RIV/68407700:21230/13:00194837 - isvavai.cz</a>
Result on the web
<a href="http://www.springerlink.com/content/p3p7388276501122/" target="_blank" >http://www.springerlink.com/content/p3p7388276501122/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-32922-7_40" target="_blank" >10.1007/978-3-642-32922-7_40</a>

Result language
angličtina
Original language name
Automatic Neonatal Sleep EEG Recognition with Social Impact based Feature Selection
Original language description
The paper presents an application of Simplified Social Impact Theory based Optimization on feature subset selection for automated neonatal sleep EEG recognition. The target classifier is 3-Nearest Neighbor classifier. We also propose a novel initialization of iterative population based optimization heuristics, which is suitable for feature subset selection, because it reduces the computational complexity of whole feature selection process and can help to prevent overfitting problems. Our methods leads to a significant reduction of the original dimensionality while simultaneously reduce the classification error.
Czech name
—
Czech description
—

Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Soft Computing Models in Industrial and Environmental Applications
ISBN
978-3-642-32921-0
ISSN
2194-5357
e-ISSN
—
Number of pages
10
Pages from-to
389-398
Publisher name
Springer
Place of publication
Heidelberg
Event location
Ostrava
Event date
Sep 5, 2012
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000312974600040

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