Comparing Non-Linear Regression Methods on Black-Box Optimization Benchmarks

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Comparing Non-Linear Regression Methods on Black-Box Optimization Benchmarks

Popis výsledku v původním jazyce

The paper compares several non-linear regression methods on synthetic data sets generated using standard benchmarks for continuous black-box optimization. For that comparison, we have chosen regression methods that have been used as surrogate models in such optimization: radial basis function networks, Gaussian processes, and random forests. Because the purpose of black-box optimization is frequently some kind of design of experiments, and because a role similar to surrogate models is in the traditionaldesign of experiments played by response surface models, we also include standard response surface models, i.e., polynomial regression. The methods are evaluated based on their mean-squared error and on the Kendall?s rank correlation coefficient betweenthe ordering of function values according to the model and according to the function used to generate the data.

Název v anglickém jazyce

Comparing Non-Linear Regression Methods on Black-Box Optimization Benchmarks

Popis výsledku anglicky

The paper compares several non-linear regression methods on synthetic data sets generated using standard benchmarks for continuous black-box optimization. For that comparison, we have chosen regression methods that have been used as surrogate models in such optimization: radial basis function networks, Gaussian processes, and random forests. Because the purpose of black-box optimization is frequently some kind of design of experiments, and because a role similar to surrogate models is in the traditionaldesign of experiments played by response surface models, we also include standard response surface models, i.e., polynomial regression. The methods are evaluated based on their mean-squared error and on the Kendall?s rank correlation coefficient betweenthe ordering of function values according to the model and according to the function used to generate the data.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings ITAT 2015: Information Technologies - Applications and Theory

ISBN

978-1-5151-2065-0

ISSN

1613-0073

e-ISSN

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Počet stran výsledku

8

Strana od-do

135-142

Název nakladatele

Technical University & CreateSpace Independent Publishing Platform

Místo vydání

Aachen & Charleston

Místo konání akce

Slovenský Raj

Datum konání akce

17. 9. 2015

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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