A Critical Look at Experimental Evaluations of EBL

Authors:
Alberto Segre;Charles Elkan;Alexander Russell
Affiliations:
Department of Computer Science, Cornell University, Ithaca, NY 14853. SEGRE@CS.CORNELL.EDU;Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA 92093. ELKAN@CS.UCSD.EDU;Department of Computer Science, Cornell University, Ithaca, NY 14853. ARUSSELL@CS.CORNELL.EDU
Venue:
Machine Learning
Year:
1991

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Abstract

A number of experimental evaluations of explanation-based learning (EBL) have been reported in the literature on machine learning. A close examination of the design of these experiments reveals certain methodological problems that could affect the conclusions drawn from the experiments. This article analyzes some of the more common methodological difficulties, and illustrates them using selected previous studies.