Imperial College London
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ProfessorStephenMuggleton

Faculty of Engineering, Department of Computing

Royal Academy Chair in Machine Learning
 
 
 
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Contact

 

+44 (0)20 7594 8307s.muggleton Website

 
 
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Assistant

 

Mrs Bridget Gundry +44 (0)20 7594 1245

 
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Location

 

407Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Schmid:2017:10.1007/978-3-319-63342-8_5,
author = {Schmid, U and Zeller, C and Besold, T and Tamaddoni-Nezhad, A and Muggleton, S},
doi = {10.1007/978-3-319-63342-8_5},
pages = {52--67},
title = {How does predicate invention affect human comprehensibility?},
url = {http://dx.doi.org/10.1007/978-3-319-63342-8_5},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses. Since predictive accuracy was readily measurable and comprehensibility not so, later definitions in the 1990s, such as that of Mitchell, tended to use a one-dimensional approach to Machine Learning based solely on predictive accuracy, ultimately favouring statistical over symbolic Machine Learning approaches. In this paper we provide a definition of comprehensibility of hypotheses which can be estimated using human participant trials. We present the results of experiments testing human comprehensibility of logic programs learned with and without predicate invention. Results indicate that comprehensibility is affected not only by the complexity of the presented program but also by the existence of anonymous predicate symbols.
AU  - Schmid,U
AU  - Zeller,C
AU  - Besold,T
AU  - Tamaddoni-Nezhad,A
AU  - Muggleton,S
DO  - 10.1007/978-3-319-63342-8_5
EP  - 67
PY  - 2017///
SN  - 0302-9743
SP  - 52
TI  - How does predicate invention affect human comprehensibility?
UR  - http://dx.doi.org/10.1007/978-3-319-63342-8_5
ER  -
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