Microarray data classifier with dimensionality reductionproximal support vector machines

DNA microarray technologies have changed the foreground of biological medicine, while the generated plentiful data is the key problem for the application of microarrays．Microarray data have the characteristics of large quantity, low sample size and high gene dimensionality. A microarray data classifier with dimensionality reduction proximal support vector machines (DRPSVM). A dimensionality reduction quadratic programming algorithm is used in DRPSVM, which shows faster training speed and smaller memory requirements than traditional PSVM does. Using CAMDA2000, colon 1 dataset and colon 2 dataset as the experimental datasets, the classification performance of DRPSVM is compared with those of BP, Nearest, RBF and SVM. DRSVM shows stable classification performance, existing one and only optimal solution and fast training which is suitable for DNA microarray data classification applications.

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