THE S2-ENSEMBLE FUSION ALGORITHM
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F11%3A86084426" target="_blank" >RIV/61989100:27740/11:86084426 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1142/S0129065711003012" target="_blank" >http://dx.doi.org/10.1142/S0129065711003012</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S0129065711003012" target="_blank" >10.1142/S0129065711003012</a>
Alternative languages
Result language
angličtina
Original language name
THE S2-ENSEMBLE FUSION ALGORITHM
Original language 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 asingle 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
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/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Neural Systems
ISSN
0129-0657
e-ISSN
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Volume of the periodical
21
Issue of the periodical within the volume
6
Country of publishing house
SG - SINGAPORE
Number of pages
20
Pages from-to
505-525
UT code for WoS article
000297557900006
EID of the result in the Scopus database
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