A comparison of accuracies obtained using 4 different classifiers and 3 different dimensionality reduction techniques, in addition to the accuracies obtained when PSDs are fed to the classifiers directly are shown.

All these accuracies are reported using hold-out testing technique. All classifiers and dimensionality reduction technique hyper-parameters are fine tuned using the grid searching algorithm. The highest accuracy obtained is 93%. It is obtained using SAE followed by SVM with RBF kernel.