Support vector machines
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.
View all articles by these authors:
Nick Guenther, Matthias Schonlau
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svmachines, svm, statistical learning, machine learning, support vector machines
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