Evolving Non-Linear Stacking Ensembles for Prediction of Go Player Attributes

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10319873" target="_blank" >RIV/00216208:11320/15:10319873 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/15:00455472
Result on the web
<a href="http://dx.doi.org/10.1109/SSCI.2015.235" target="_blank" >http://dx.doi.org/10.1109/SSCI.2015.235</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SSCI.2015.235" target="_blank" >10.1109/SSCI.2015.235</a>

Result language
angličtina
Original language name
Evolving Non-Linear Stacking Ensembles for Prediction of Go Player Attributes
Original language description
The paper presents an application of non-linear stacking ensembles for prediction of Go player attributes. An evolutionary algorithm is used to form a diverse ensemble of base learners, which are then aggregated by a stacking ensemble. This methodology allows for an efficient prediction of different attributes of Go players from sets of their games. These attributes can be fairly general, in this work, we used the strength and style of the players.
Czech name
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Czech description
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Project
<a href="/en/project/GA15-18108S" target="_blank" >GA15-18108S: Model complexity of neural, radial, and kernel networks</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Computational Intelligence, 2015 IEEE Symposium Series on
ISBN
978-1-4799-7560-0
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1673-1680
Publisher name
IEEE
Place of publication
Neuveden
Event location
Cape Town, JAR
Event date
Dec 7, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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