Improving K-means Clustering with Genetic Programming for Feature Construction
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Lensen:2017:GECCOa,
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author = "Andrew Lensen and Bing Xue and Mengjie Zhang",
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title = "Improving K-means Clustering with Genetic Programming
for Feature Construction",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference Companion",
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series = "GECCO '17",
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year = "2017",
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isbn13 = "978-1-4503-4939-0",
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address = "Berlin, Germany",
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pages = "237--238",
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size = "2 pages",
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URL = "http://doi.acm.org/10.1145/3067695.3075962",
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DOI = "doi:10.1145/3067695.3075962",
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acmid = "3075962",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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keywords = "genetic algorithms, genetic programming, cluster
analysis, evolutionary computation, feature
construction, k-means",
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month = "15-19 " # jul,
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abstract = "k-means is one of the most commonly used clustering
algorithms in data mining. Despite this, it has a
number of fundamental limitations which prevent it from
performing effectively on large or otherwise difficult
datasets. A common technique to improve performance of
data mining algorithms is feature construction, a
technique which combines features together to produce
more powerful constructed features that can improve the
performance of a given algorithm. Genetic Programming
(GP) has been used for feature construction very
successfully, due to its program-like structure. This
paper proposes two representations for using GP to
perform feature construction to improve the performance
of k-means, using a wrapper approach. Our results show
significant improvements in performance compared to
k-means using all original features across six
difficult datasets.",
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notes = "Also known as \cite{Lensen:2017:IKM:3067695.3075962}
GECCO-2017 A Recombination of the 26th International
Conference on Genetic Algorithms (ICGA-2017) and the
22nd Annual Genetic Programming Conference (GP-2017)",
- }
Genetic Programming entries for
Andrew Lensen
Bing Xue
Mengjie Zhang
Citations