Support vector machines

Nick Guenther () and Matthias Schonlau ()
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Nick Guenther: University of Waterloo
Matthias Schonlau: University of Waterloo

Stata Journal, 2016, vol. 16, issue 4, 917-937

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. Copyright 2016 by StataCorp LP.

Keywords: svmachines; svm; statistical learning; machine learning; support vector machines (search for similar items in EconPapers)
Date: 2016
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