Abstract
The investigation of 16 fuzzy algorithms implemented in data mining system KEEL from the point of view of their usefulness to create bagging ensemble models to assist with real estate appraisal were presented in the paper. All the experiments were conducted with a real-world dataset derived from a cadastral system and registry of real estate transactions. The results showed there were significant differences in accuracy between individual algorithms. The analysis of measures of error diversity revealed that only the highest values of an average pairwise correlation of outputs were a profitable criterion for the selection of ensemble members.
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Krzystanek, M., Lasota, T., Telec, Z., Trawiński, B. (2010). Analysis of Bagging Ensembles of Fuzzy Models for Premises Valuation. In: Nguyen, N.T., Le, M.T., Świątek, J. (eds) Intelligent Information and Database Systems. ACIIDS 2010. Lecture Notes in Computer Science(), vol 5991. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12101-2_34
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