Nonparametric statistical analysis of machine learning algorithms for regression problems

Authors:
Magdalena Graczyk;Tadeusz Lasota;Zbigniew Telec;Bogdan Trawiński
Affiliations:
Wrocław University of Technology, Institute of Informatics, Wrocław, Poland;Wroclaw 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
Venue:
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Year:
2010

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Abstract

Several experiments aimed to apply recently proposed statistical procedures which are recommended for analysing multiple 1×n and n×n comparisons of machine learning algorithms were conducted. 11 regression algorithms comprising 5 deterministic and 6 neural network ones implemented in the data mining system KEEL were employed. All experiments were performed using 29 benchmark datasets for regression. The investigation proved the usefulness and strength of multiple comparison statistical procedures to analyse and select machine learning algorithms.