2011-04-13T02:10:46-07:00
Resource:svmvia
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http://noble.gs.washington.edu/proj/svmvia/
svmvia implements the full regularization path optimization algorithm for training a support vector machine.
The support vector machine algorithm has a single hyperparameter C that regularizes the learned model. Recently, Hastie et al. (2004) described an algorithm for finding the SVM solution for all possible values of this regularization parameter. We present an efficient C++ implementation of this algorithm called svmvia. We compare svmvia running time to that of libsvm on three simulated and two real data sets. Depending upon the data set, for small values of C svmvia can take approximately 10-1000 times as long as libsvm. However, for large values of C, it is often faster to find the entire regularization path than to train a single model.
nlx_23153
Resource:svmvia
2011-04-12T00:00:00
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University of Washington; Washington; USA
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