Songbin Zhou

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2.6. Methods for Comparison OCSVM [22]: The one-class support vector machine (OCSVM) tries to learn a hypersphere in the feature space that maps most of the training data into it. The spectra of effective pixels were averaged, and the obtained mean spectra were used as the inputs of the OCSVM models. The radial basis function (RBF) was adopted as the kernel function, and the boundary hyperparameter υ was searched in the range of [0.01, 0.02, 0.03, 0.04, 0.05, 0.1, 0.2, 0.3] to maximize the AUC.