Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Automated design process for hybrid regression modeling with a one-class SVM

Automated design process for hybrid regression modeling with a one-class SVM AbstractThe accuracy of many regression models suffers from inhomogeneous data coverage. Models loose accuracy because they are unable to locally adapt the model complexity. This article develops and evaluates an automated design process for the generation of hybrid regression models from arbitrary submodels. For the first time, these submodels are weighted by a One-Class Support Vector Machine, taking local data coverage into account. Compared to reference regression models, the newly developed hybrid models achieve significant better results in nine out of ten benchmark datasets. To enable straightforward usage in data science, an implementation is integrated in the open source MATLAB toolbox SciXMiner. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png at - Automatisierungstechnik de Gruyter

Automated design process for hybrid regression modeling with a one-class SVM

Loading next page...
 
/lp/de-gruyter/automated-design-process-for-hybrid-regression-modeling-with-a-one-yrZWztKM3f
Publisher
de Gruyter
Copyright
© 2019 Walter de Gruyter GmbH, Berlin/Boston
ISSN
2196-677X
eISSN
2196-677X
DOI
10.1515/auto-2019-0013
Publisher site
See Article on Publisher Site

Abstract

AbstractThe accuracy of many regression models suffers from inhomogeneous data coverage. Models loose accuracy because they are unable to locally adapt the model complexity. This article develops and evaluates an automated design process for the generation of hybrid regression models from arbitrary submodels. For the first time, these submodels are weighted by a One-Class Support Vector Machine, taking local data coverage into account. Compared to reference regression models, the newly developed hybrid models achieve significant better results in nine out of ten benchmark datasets. To enable straightforward usage in data science, an implementation is integrated in the open source MATLAB toolbox SciXMiner.

Journal

at - Automatisierungstechnikde Gruyter

Published: Oct 25, 2019

References