Multi-Objective Gene Expression Programming for Clustering
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- @Article{journals/itc/ZhengJC12,
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title = "Multi-Objective Gene Expression Programming for
Clustering",
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author = "Yifei Zheng and Lixin Jia and Hui Cao",
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journal = "ITC",
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year = "2012",
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number = "3",
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volume = "41",
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pages = "283--294",
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keywords = "genetic algorithms, genetic programming, gene
expression programming, Clustering, multi-objective,
evolutionary algorithm",
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bibdate = "2014-01-30",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/itc/itc41.html#ZhengJC12",
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URL = "http://dx.doi.org/10.5755/j01.itc.41.3.1330",
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URL = "http://www.itc.ktu.lt/index.php/ITC/article/view/1330",
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DOI = "doi:10.5755/j01.itc.41.3.1330",
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abstract = "This paper proposes a multi-objective gene expression
programming for clustering (MGEPC), which could
automatically determine the number of clusters and the
appropriate partitioning from the data set. The
clustering algebraic operations of gene expression
programming are extended first. Then based on the
framework of the Non-dominated Sorting Genetic
Algorithm-II, two enhancements are proposed in MGEPC.
First, a multi-objective k-means clustering is proposed
for local search, where the total symmetrical
compactness and the cluster connectivity are used as
two complementary objectives and the point symmetry
based distance is adopted as the distance metric.
Second, the power-law distribution based selection
strategy is proposed for the parent population
generation. In addition, the external archive and the
archive truncation are used to keep a historical record
of the non-dominated solutions found along the search
process. Experiments are performed on five artificial
and three real-life data sets. Results show that the
proposed algorithm outperforms the PESA-II based
clustering method (MOCK), the archived multiobjective
simulated annealing based clustering technique with
point symmetry based distance (VAMOSA) and the
single-objective version of gene expression programming
based clustering technique (GEP-Cluster).",
- }
Genetic Programming entries for
Yifei Zheng
Lixin Jia
Hui Cao
Citations