Improvement of neural network classifier using floating centroids
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86092949" target="_blank" >RIV/61989100:27240/12:86092949 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s10115-011-0410-8" target="_blank" >http://dx.doi.org/10.1007/s10115-011-0410-8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10115-011-0410-8" target="_blank" >10.1007/s10115-011-0410-8</a>
Alternative languages
Result language
angličtina
Original language name
Improvement of neural network classifier using floating centroids
Original language description
This paper presents a novel technique-Floating Centroids Method (FCM) designed to improve the performance of a conventional neural network classifier. Partition space is a space that is used to categorize data sample after sample is mapped by neural network. In the partition space, the centroid is a point, which denotes the center of a class. In a conventional neural network classifier, position of centroids and the relationship between centroids and classes are set manually. In addition, number of centroids is fixed with reference to the number of classes. The proposed approach introduces many floating centroids, which are spread throughout the partition space and obtained by using K-Means algorithm. Moreover, different classes labels are attached tothese centroids automatically. A sample is predicted as a certain class if the closest centroid of its corresponding mapped point is labeled by this class. Experimental results illustrate that the proposed method has favorable performance
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA201%2F09%2F0990" target="_blank" >GA201/09/0990: XML data processing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Knowledge and Information Systems
ISSN
0219-1377
e-ISSN
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Volume of the periodical
31
Issue of the periodical within the volume
3
Country of publishing house
GB - UNITED KINGDOM
Number of pages
22
Pages from-to
433-454
UT code for WoS article
000304116100002
EID of the result in the Scopus database
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