Comparing SVM, Gaussian Process and Random Forest Surrogate Models for the CMA-ES
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00447920" target="_blank" >RIV/67985807:_____/15:00447920 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Comparing SVM, Gaussian Process and Random Forest Surrogate Models for the CMA-ES
Original language description
In practical optimization tasks, it is more and more frequent that the objective function is black-box which means that it cannot be described mathematically. Such functions can be evaluated only empirically, usually through some costly or time-consumingmeasurement, numerical simulation or experimental testing. Therefore, an important direction of research is the approximation of these objective functions with a suitable regression model, also called surrogate model of the objective functions. This paper evaluates two different approaches to the continuous black-box optimization which both integrates surrogate models with the state-of-the-art optimizer CMAES. The first Ranking SVM surrogate model estimates the ordering of the sampled points as the CMA-ES utilizes only the ranking of the fitness values. However, we show that continuous Gaussian processes model provides in the early states of the optimization comparable results.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA13-17187S" target="_blank" >GA13-17187S: Constructing Advanced Comprehensible Classifiers</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings ITAT 2015: Information Technologies - Applications and Theory
ISBN
978-1-5151-2065-0
ISSN
1613-0073
e-ISSN
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Number of pages
8
Pages from-to
186-193
Publisher name
Technical University & CreateSpace Independent Publishing Platform
Place of publication
Aachen & Charleston
Event location
Slovenský Raj
Event date
Sep 17, 2015
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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