Investigation of rotation forest ensemble method using genetic fuzzy systems for a regression problem

Authors:
Tadeusz Lasota;Zbigniew Telec;Bogdan Trawiński;Grzegorz Trawiński
Affiliations:
Dept. of Spatial Management, Wrocław University of Environmental and Life Sciences, Wrocław, Poland;Institute of Informatics, Wrocław University of Technology, Wrocław, Poland;Institute of Informatics, Wrocław University of Technology, Wrocław, Poland;Faculty of Electronics, Wrocław University of Technology, Wrocław, Poland
Venue:
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
Year:
2012

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Abstract

The rotation forest ensemble method using a genetic fuzzy rule-based system as a base learning algorithm was developed in Matlab environment. The method was applied to the real-world regression problem of predicting the prices of residential premises based on historical data of sales/purchase transactions. The computationally intensive experiments were conducted aimed to compare the accuracy of ensembles generated by our proposed method with bagging, repeated holdout, and repeated cross-validation models. The statistical analysis of results was made employing nonparametric Friedman and Wilcoxon statistical tests.