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Gene Selection for Cancer Classification using Support Vector Machines

Isabelle Guyon^{a b}✉, Jason Weston^{a c}, Stephen D. Barnhill^{a c}, Vladimir N. Vapnik^{d e}✉

^aSavannah, Georgia, USA
^bBarnhill Bioinformatics, Savannah, Georgia, USA. isabelle@barnhilltechnologies.com#TAB#
^cBarnhill Bioinformatics, Savannah, Georgia, USA#TAB#
^dAT&T Labs, Red Bank, New Jersey, USA
^eAT&T Labs, Red Bank, New Jersey, USA. vlad@research.att.com#TAB#
✉Corresponding author

Machine Learning Springer Science+Business Media2002-01-01 9,947 citations48 references

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TL;DRThis paper proposes a new method of gene selection utilizing Support Vector Machine methods based on Recursive Feature Elimination (RFE), and demonstrates experimentally that the genes selected yield better classification performance and are biologically relevant to cancer. (Semantic Scholar)

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Gene Selection for Cancer Classification using Support Vector Machines

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