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.
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Lasota, T., Telec, Z., Trawiński, B., Trawiński, G. (2012). Investigation of Rotation Forest Ensemble Method Using Genetic Fuzzy Systems for a Regression Problem. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7196. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28487-8_41
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DOI: https://doi.org/10.1007/978-3-642-28487-8_41
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