<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "C-KPCA: Custom Kernel PCA for Cancer Classification"^^ . "Abstract Principal component analysis (PCA) is an effective and well-known method for reducing high-dimensional data sets. Recently, KPCA (Kernel PCA), a nonlinear form of PCA, has been introduced into many fields. In this paper, we propose a new gene selection, namely Custom Kernel principal component analysis (C-KPCA). The new kernel function for KPCA is created by combining a set of kernel functions. First, Singular Value Decomposition (SVD) is used to reduce the dimension of microarray data. Input space is then mapped to ..."^^ . "2016-07" . . "Springer International Publishing"^^ . . "Springer International Publishing"^^ . . . . . . . . . . . "Van Sang"^^ . "Ha"^^ . "Van Sang Ha"^^ . . "Ha Nam"^^ . "Nguyen"^^ . "Ha Nam Nguyen"^^ . . . . . "HTML Summary of #1941 \n\nC-KPCA: Custom Kernel PCA for Cancer Classification\n\n" . "text/html" . . . "Information Technology (IT)"@en . .