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S. Mukherjee, P. Tamayo, J.P. Mesirov, D. Slonim, A. Verri, and T. Poggio (1999)

Support Vector Machine Classification of Microarray Data


An effective approach to cancer classification based upon gene expression monitoring using DNA microarrays was introduced by Golub et. al. The main problem they faced was accurately assigning leukemia samples the class labels acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL). We used a Support Vector Machine (SVM) classifier to assign these labels. The motivation for the use of a SVM is that DNA microarray problems can be very high dimensional and have very few training data. This type of situation is particularly well suited for an SVM approach. We achieve slightly better performance on this (simple) classification task than Golub et. al.

by admin last modified 2007-01-31 11:08

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