A Critical Look at Experimental Evaluations of EBL

Alberto Segre; Charles Elkan; Alexander Russell

doi:10.1023/A:1022658420943

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A Critical Look at Experimental Evaluations of EBL

Journal article

Open access

Peer reviewed

A Critical Look at Experimental Evaluations of EBL

Alberto Segre, Charles Elkan and Alexander Russell

Machine learning, Vol.6(2), p.183

03/01/1991

DOI: 10.1023/A:1022658420943

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Abstract

Byline: Alberto Segre (1), Charles Elkan (2), Alexander Russell (3) Keywords: Explanation-based learning; speedup learning; performance measures 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. Author Affiliation: Article History: Registration Date: 13/01/2005

Details

Title: Subtitle: A Critical Look at Experimental Evaluations of EBL
Creators: Alberto Segre - Cornell University
Charles Elkan - University of California San Diego
Alexander Russell - Cornell University
Resource Type: Journal article
Publication Details: Machine learning, Vol.6(2), p.183
DOI: 10.1023/A:1022658420943
ISSN: 0885-6125
eISSN: 1573-0565
Publisher: Springer
Language: English
Date published: 03/01/1991
Description audience: Academic
Academic Unit: Nursing; Fraternal Order of Eagles Diabetes Research Center; Computer Science
Record Identifier: 9984259489602771

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