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Guidelines for defining benchmark problems in Genetic Programming
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| File | Description | Size | Format | |
|---|---|---|---|---|
| benchmarks.pdf | 508.82 kB | Adobe PDF | Download |
| Title: | Guidelines for defining benchmark problems in Genetic Programming | Authors: | Nicolau, Miguel Agapitos, Alexandros O'Neill, Michael Brabazon, Anthony |
Permanent link: | http://hdl.handle.net/10197/8249 | Date: | 28-May-2015 | Online since: | 2017-01-04T12:52:33Z | 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 CASL Research Collection |
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