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A patient-specific seizure prediction algorithm is proposed using a classifier to differentiate preictal from interictal ECoG signals. Spectral power of ECoG processed in four different fashions are used as features: raw, time-differential, space-differential, and time/space-differential ECoG. The features are classified using cost-sensitive support vector machines by the double cross-validation methodology...
The important issue in multi-class classification on support vector machines is the decision rule, which determines whether an input pattern belongs to a predicted class. To enhance the accuracy of multi-class classification, this study proposes a multi-weighted majority voting algorithm of support vector machine (SVM), and applies it to overcome complex facial security application. The proposed algorithm...
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