Abstract
The ensemble methods combining resampling techniques: cross-validation, repeated holdout, and bootstrap sampling with clustering and random oracle using a genetic fuzzy rule-based system as a base learning algorithm were developed in Matlab environment. The methods were 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 the proposed methods with different number of clusters or random oracle subsets. 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. (2013). Experimental Evaluation of Resampling Combined with Clustering and Random Oracle Using Genetic Fuzzy Systems. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) Multimedia and Internet Systems: Theory and Practice. Advances in Intelligent Systems and Computing, vol 183. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32335-5_13
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DOI: https://doi.org/10.1007/978-3-642-32335-5_13
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