SVM::crossvalidateTest training params on subsets of the training data. Description
public float svm::crossvalidate
( array
$problem
, int $number_of_folds
)Crossvalidate can be used to test the effectiveness of the current parameter set on a subset of the training data. Given a problem set and a n "folds", it separates the problem set into n subsets, and the repeatedly trains on one subset and tests on another. While the accuracy will generally be lower than a SVM trained on the enter data set, the accuracy score returned should be relatively useful, so it can be used to test different training parameters. Parameters
Return ValuesThe correct percentage, expressed as a floating point number from 0-1. In the case of NU_SVC or EPSILON_SVR kernels the mean squared error will returned instead. See Also
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