Guidelines for defining benchmark problems in Genetic Programming
|Title:||Guidelines for defining benchmark problems in Genetic Programming||Authors:||Nicolau, Miguel
|Permanent link:||http://hdl.handle.net/10197/8249||Date:||28-May-2015||Abstract:||The field of Genetic Programming has recently seen a surge of attention to the fact that benchmarking and comparison of approaches is often done in non-standard ways, using poorly designed comparison problems. We raise some issues concerning the design of benchmarks, within the domain of symbolic regression, through experimental evidence. A set of guidelines is provided, aiming towards careful definition and use of artificial functions as symbolic regression benchmarks.||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2015 IEEE||Keywords:||Genetic programming;Benchmarks;Symbolic regression;Regression;Model building||DOI:||10.1109/CEC.2015.7257019||Language:||en||Status of Item:||Peer reviewed||Conference Details:||IEEE Congress on Evolutionary Computation, CEC 2015, Sendai, Japan, May 25-28, 2015, Proceedings, Sendai, Japan, May, 2015|
|Appears in Collections:||Business Research Collection|
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