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Wrapper feature selection algorithm based on MA-LSSVM


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Wrapper feature selection algorithm based on MA-LSSVM
Lin QiZhang HongLi Qianmu
School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
feature selection memetic algorithm least squares support vector machine high dimensional small sample data machine learning global search local search
To improve the feature selection problem of the high dimensional small sample data,this paper combines memetic algorithm(MA)and least squares support vector machine(LS-SVM)to design a wrapper feature selection method(MA-LSSVM).The solving strategy of the proposed method is composed by global search and local search,which utilizes the speciality of being easy to search optimal solution to construct classifiers and to regard classification accuracy as the main component of memetic algorithm fitness function in the optimization process.The experimental results demonstrate that the MA-LSSVM can be more efficient and stable to obtain features larger contribution to the classification precision,reducing the data dimension and improving the classification efficiency.


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Last Update: 2016-02-29