About: Improvement of neural network classifier using floating centroids

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
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 to these 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 especially with respect to the training accuracy, generalization accuracy, and average F-measures. 2011 Springer-Verlag London Limited. 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 to these 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 especially with respect to the training accuracy, generalization accuracy, and average F-measures. 2011 Springer-Verlag London Limited. (en)
Title	Improvement of neural network classifier using floating centroids Improvement of neural network classifier using floating centroids (en)
skos:prefLabel	Improvement of neural network classifier using floating centroids Improvement of neural network classifier using floating centroids (en)
skos:notation	RIV/61989100:27240/12:86092949!RIV15-GA0-27240___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GA201/09/0990)
http://linked.open...iv/cisloPeriodika	3
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Abraham Padath, Ajith
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / Fakulta elektrotechniky a informatiky
http://linked.open...dnocenehoVysledku	140928
http://linked.open...ai/riv/idVysledku	RIV/61989100:27240/12:86092949
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Neural networks; Floating Centroids Method; Classification (en)
http://linked.open.../riv/klicoveSlovo	Floating Centroids Method Classification Neural networks
http://linked.open...odStatuVydavatele	GB - Spojené království Velké Británie a Severního Irska
http://linked.open...ontrolniKodProRIV	[BD48F8ADEF9E]
http://linked.open...i/riv/nazevZdroje	Knowledge and Information Systems
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	7 (xsd:int)
http://linked.open...vavai/riv/projekt	XML data processing
http://linked.open...UplatneniVysledku	2012
http://linked.open...v/svazekPeriodika	31
http://linked.open...iv/tvurceVysledku	Abraham Padath, Ajith Wang, H. Wang, L. Chen, Z. Sun, H. Chen, Y. Yang, B.
http://linked.open...ain/vavai/riv/wos	000304116100002
issn	0219-1377
number of pages	22 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/s10115-011-0410-8
http://localhost/t...ganizacniJednotka	27240

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