Gene Selection and Classification by Partial Least Squares and Principal component analysis

부분최소자승법과 주성분분석을 이용한 유전자 선택과 분류

  • Published : 2001.10.01

Abstract

DNA chip technology enables us to monitor thousands of gene expressions per sample simultaneously. Typically, DNA microarray data has at least several thousands of variables (genes) wish relatively smal1 number of samples. Thus feature (gene) selection by dimensionality reduction is necessary for efficient data analysis. In this paper we employ the partial least squares (PLS) method for gene selection and the principal component analysis (PCA) method for classification. The useful behavior of the PLS is verified by computer simulations.

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