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Classification performance (AUC and G-Mean) of the SVM while classifying RBANS (left) and TUG (right) clinical scores when the SVM is trained using features that are derived from randomly-annotated activities. We use the complete feature set to train the SVMs and discretize the clinical assessment scores into two classes.
