Shi Chao, Chen Lihui, in Proceedings of the 3rd Asia-Pacific Bioinformatics Conference, Advances in Bioinformatics and Computational Biology, vol. 1, 2005. download!
Abstract
Abstract
Cancer classification is one major application of Microarray data analysis. Due to the ultra high dimensionality nature of microarray data, data Dimension Reduction has drawn special attention for such type of data analysis. The currently available data dimension reduction methods are either supervised, where data need to be labeled, or computational complex. In this paper, we proposed to use a revised Locally Linear embedding(LLE) method, which is purely unsupervised and fast as the feature extraction strategy for microarray data analysis. Three public available microarray datasets have been used to test the proposed method. The effectiveness of LLE is evaluated by the classification accuracy of a SVM classifier. Generally, the results are promising.
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