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

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. © 2012 Springer-Verlag.