A study on Koza's performance measures
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- @Article{Barrero:2015:GPEM,
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author = "David F. Barrero and Bonifacio Castano and
Maria D. R-Moreno and David Camacho",
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title = "A study on Koza's performance measures",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2015",
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volume = "16",
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number = "3",
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pages = "327--349",
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month = sep,
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keywords = "genetic algorithms, genetic programming, Computational
effort, Performance measures, Experimental methods,
Measurement error",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-014-9238-9",
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size = "23 pages",
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abstract = "John R. Koza defined several metrics to measure the
performance of an Evolutionary Algorithm that have been
widely used by the Genetic Programming community.
Despite the importance of these metrics, and the doubts
that they have generated in many authors, their
reliability has attracted little research attention,
and is still not well understood. The lack of knowledge
about these metrics has likely contributed to the
decline in their usage in the last years. This paper is
an attempt to increase the knowledge about these
measures, exploring in which circumstances they are
more reliable, providing some clues to improve how they
are used, and eventually making their use more
justifiable. Specifically, we investigate the amount of
uncertainty associated with the measures, taking an
analytical and empirical approach and reaching
theoretical boundaries to the error. Additionally, a
new method to calculate Koza's performance measures is
presented. It is shown that these metrics, under common
experimental configurations, have an unacceptable
error, which can be arbitrary large in certain
conditions.",
- }
Genetic Programming entries for
David F Barrero
Bonifacio Castano
Ma Dolores Rodriguez Moreno
David Camacho
Citations