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The Stata Journal
Volume 16 Number 4: pp. 917-937

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Support vector machines

Nick Guenther
University of Waterloo
Waterloo, Canada
[email protected]
Matthias Schonlau
University of Waterloo
Waterloo, Canada
[email protected]
Abstract.  Support vector machines are statistical- and machine-learning techniques with the primary goal of prediction. They can be applied to continuous, binary, and categorical outcomes analogous to Gaussian, logistic, and multinomial regression. We introduce a new command for this purpose, svmachines. This package is a thin wrapper for the widely deployed libsvm (Chang and Lin, 2011, ACM Transactions on Intelligent Systems and Technology 2(3): Article 27). We illustrate svmachines with two examples.
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