Optimization of morphological data in numerical taxonomy analysis using genetic algorithms feature selection method
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Dosyalar
Tarih
2009
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Association for Computing Machinery
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Studies in Numerical Taxonomy are carried out by measuring characters as much as possible. The workload over scientists and labor to perform measurements will increase proportionally with the number of variables (or characters) to be used in the study. However, some part of the data may be irrelevant or sometimes meaningless. Here in this study, we introduce an algorithm to obtain a subset of data with minimum characters that can represent original data. Morphological characters were used in optimization of data by Genetic Algorithms Feature Selection method. The analyses were performed on an 18 character?11 taxa data matrix with standardized continuous characters. The analyses resulted in a minimum set of 2 characters, which means the original tree based on the complete data can also be constructed by those two characters. © 2009 Copyright is held by the author/owner(s).
Açıklama
ACM SIGEVO
11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 -- 8 July 2009 through 12 July 2009 -- Montreal, QC -- 78693
11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 -- 8 July 2009 through 12 July 2009 -- Montreal, QC -- 78693
Anahtar Kelimeler
Biological Data Mining, Genetic Algorithms, Morphological Data, Optimization, Phylogenetics
Kaynak
Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
2009-January
