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Distance preserving dimension reduction (DPDR) using the singular value decomposition has recently been introduced. In this paper, for disease diagnosis using gene or protein expression data, we present empirical comparison results between DPDR and other various dimension reduction (DR) methods (i.e. PC A, MDS, Isomap, and LLE) when using support vector machines with radial basis function kernel....
Dimension reduction plays an important role in handling the massive quantity of high dimensional data such as biomedical text data, gene expression data, and mass spectrometry data, and so forth. In this paper, we introduce distance preserving dimension reduction (DPDR) based on the QR factorization (DPDR/QR) or the Cholesky factorization (DPDR/C). DPDR generates lower dimensional representations...
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