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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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Nick Guenther
Matthias Schonlau
The Stata Journal Promoting communications on statistics and Stata
University of Waterloo
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Guenther et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69da2494ba6014a02e836085 — DOI: https://doi.org/10.1177/1536867x1601600407