Exploration of bagging ensembles comprising genetic fuzzy models to assist with real estate appraisals

Authors:
Tadeusz Lasota;Zbigniew Telec;Bogdan Trawiński;Krzysztof Trawiński
Affiliations:
Wrocław University of Environmental and Life Sciences, Dept. of Spatial Management, Wroclaw, Poland;Wrocław University of Technology, Institute of Informatics, Wrocław, Poland;Wrocław University of Technology, Institute of Informatics, Wrocław, Poland;European Centre for Soft Computing, Mieres, Asturias, Spain
Venue:
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Year:
2009

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Abstract

The study reported was devoted to investigate to what extent bagging approach could lead to the improvement of the accuracy machine learning regression models. Four algorithms implemented in the KEEL tool, including two evolutionary fuzzy systems, decision trees for regression, and neural network, were used in the experiments. The results showed that some bagging ensembles ensured higher prediction accuracy than single models.