A genetic programming-based approach to the classification of multiclass microarray datasets | Zendy

Kunhong Liu | Zendy; Chungui Xu | Zendy

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A genetic programming-based approach to the classification of multiclass microarray datasets

Author(s) -

Kunhong Liu,

Chungui Xu

Publication year - 2008

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btn644

Subject(s) - multiclass classification , computer science , genetic programming , set (abstract data type) , class (philosophy) , feature selection , artificial intelligence , selection (genetic algorithm) , machine learning , feature (linguistics) , genetic algorithm , construct (python library) , data mining , support vector machine , philosophy , programming language , linguistics

Feature selection approaches have been widely applied to deal with the small sample size problem in the analysis of micro-array datasets. For the multiclass problem, the proposed methods are based on the idea of selecting a gene subset to distinguish all classes. However, it will be more effective to solve a multiclass problem by splitting it into a set of two-class problems and solving each problem with a respective classification system.

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