Podejście wielomodelowe w regresji danych symbolicznych interwałowych

• Authors: Pełka Marcin

Title variants

EN

Ensemble learning in regression model of symbolic interval data

• Languages of publication: PL

Abstracts

EN

Ensemble learning, which consist in using a lot of models (instead one single model) can be used in classical data analysis. The aim of the paper is to present an adaptation of ensemble learning with the use of bagging for regression analysis of symbolic interval-valued data. The article presents basic concepts concerning symbolic data analysis, the adaptation of ordinary least squares model for symbolic interval-valued data and the idea of bagging approach in ensemble learning. The empirical part contains the results of simulation studies obtained with the application of real and artificial data sets for centers and centers and range methods. The results show that both methods reach usually better results when using bagging than in case of a single model.

Keywords

EN

ensemble learning; regression of symbolic data; interval-valued data

• Publisher: Uniwersytet Ekonomiczny we Wrocławiu. Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Econometrics. Ekonometria. Advances in Applied Data Analytics
• Year: 2014
• Issue: 4(46)
• Pages: 211-220

Contributors

author

Pełka Marcin

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