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Erschienen in:
2018 | OriginalPaper | Buchkapitel
On a New Method of Dynamic Integration of Fuzzy Linear Regression Models
verfasst von : Jakub Kozerski, Marek Kurzynski
Erschienen in: Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017
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Abstract
In the study the problem of ensemble regression with fuzzy linear regression (FLR) models is considered. For this case a novel method of integration is proposed in which first fuzzy responses of base FLR models are integrated and next the fuzzy response of a common model is defuzzified. Four different operators are defined for integration procedure. The performance of proposed integration methods of FLR base models on the soft level were compared against state-of-the-art integration method on the crisp level using computer generated datasets with linear, 2-order and 3-order models and different variances of Gaussian disturbances. As a criterion of method quality the root mean square error was applied. The results of computer experiments clearly show that in many cases proposed methods significant outperform the reference approach.