- author = "W. B. Langdon and J. P. Nordin",
- title = "Seeding {GP} Populations",
- booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
- year = "2000",
- editor = "Riccardo Poli and Wolfgang Banzhaf and William B. Langdon and Julian F. Miller and Peter Nordin and Terence C. Fogarty",
- volume = "1802",
- series = "LNCS",
- pages = "304--315",
- address = "Edinburgh",
- publisher_address = "Berlin",
- month = "15-16 " # apr,
- organisation = "EvoNet",
- publisher = "Springer-Verlag",
- keywords = "genetic algorithms, genetic programming, Pareto multi-objective fitness: Poster",
- ISBN = "3-540-67339-3",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL_eurogp2000_seed.pdf",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL_eurogp2000_seed.ps.gz",
-
DOI = "
doi:10.1007/978-3-540-46239-2_23",
-
video_url = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/benelearn99/27-sep-99.5-oct.vanP5000.101-animation.gif",
- size = "12 pages",
- abstract = "We show GP populations can evolve from perfect programs which match the training material under the influence of a Pareto multi-objective fitness and program size selection scheme to generalise. The technique is demonstrated upon programmatic image compression, two machine learning benchmark problems (Pima Diabetes and Wisconsin Breast Cancer) and a consumer profiling task (Benelearn99).",
-
notes = "Benelearn99 binary classification caravan insurance
dataset includes missing data, it now forms CoIL-2000
https://archive.ics.uci.edu/ml/datasets/Insurance+Company+Benchmark+%28COIL+2000%29
https://liacs.leidenuniv.nl/~puttenpwhvander/library/cc2000/
27-sep-99.5-oct.vanP5000.101-animation.gif from \cite{langdon:1999:benelearn1}
EuroGP'2000, part of \cite{poli:2000:GP}",
