About: THE S2-ENSEMBLE FUSION ALGORITHM

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	This paper presents a novel model for performing classification and visualization of high-dimensional data by means of combining two enhancing techniques. The first is a semi-supervised learning, an extension of the supervised learning used to incorporate unlabeled information to the learning process. The second is an ensemble learning to replicate the analysis performed, followed by a fusion mechanism that yields as a combined result of previously performed analysis in order to improve the result of a single model. The proposed learning schema, termed S2-Ensemble, is applied to several unsupervised learning algorithms within the family of topology maps, such as the Self-Organizing Maps and the Neural Gas. This study also includes a thorough research of the characteristics of these novel schemes, by means quality measures, which allow a complete analysis of the resultant classifiers from the viewpoint of various perspectives over the different ways that these classifiers are used. The study conducts empirical evaluations and comparisons on various real-world datasets from the UCI repository, which exhibit different characteristics, so to enable an extensive selection of situations where the presented new algorithms can be applied. This paper presents a novel model for performing classification and visualization of high-dimensional data by means of combining two enhancing techniques. The first is a semi-supervised learning, an extension of the supervised learning used to incorporate unlabeled information to the learning process. The second is an ensemble learning to replicate the analysis performed, followed by a fusion mechanism that yields as a combined result of previously performed analysis in order to improve the result of a single model. The proposed learning schema, termed S2-Ensemble, is applied to several unsupervised learning algorithms within the family of topology maps, such as the Self-Organizing Maps and the Neural Gas. This study also includes a thorough research of the characteristics of these novel schemes, by means quality measures, which allow a complete analysis of the resultant classifiers from the viewpoint of various perspectives over the different ways that these classifiers are used. The study conducts empirical evaluations and comparisons on various real-world datasets from the UCI repository, which exhibit different characteristics, so to enable an extensive selection of situations where the presented new algorithms can be applied. (en)
Title	THE S2-ENSEMBLE FUSION ALGORITHM THE S2-ENSEMBLE FUSION ALGORITHM (en)
skos:prefLabel	THE S2-ENSEMBLE FUSION ALGORITHM THE S2-ENSEMBLE FUSION ALGORITHM (en)
skos:notation	RIV/61989100:27740/11:86084426!RIV13-MSM-27740___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(ED1.1.00/02.0070)
http://linked.open...iv/cisloPeriodika	06
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Corchado, Emilio
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 / IT4Innovations
http://linked.open...dnocenehoVysledku	234130
http://linked.open...ai/riv/idVysledku	RIV/61989100:27740/11:86084426
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	growing neural gas; self-organization; ensemble learning; Semi-supervised learning (en)
http://linked.open.../riv/klicoveSlovo	self-organization Semi-supervised learning ensemble learning growing neural gas
http://linked.open...odStatuVydavatele	SG - Singapurská republika
http://linked.open...ontrolniKodProRIV	[F529B69F9CEE]
http://linked.open...i/riv/nazevZdroje	International Journal of Neural Systems
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	IT4Innovations Centre of Excellence
http://linked.open...UplatneniVysledku	2011
http://linked.open...v/svazekPeriodika	21
http://linked.open...iv/tvurceVysledku	Baruque, Bruno Corchado, Emilio Hujun, Yin
http://linked.open...ain/vavai/riv/wos	000297557900006
issn	0129-0657
number of pages	20 (xsd:int)
http://bibframe.org/vocab/doi	10.1142/S0129065711003012
http://localhost/t...ganizacniJednotka	27740

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