Dysphonic Voice Pattern Analysis of Patients in Parkinson’s Disease Using Minimum Interclass Probability Risk Feature Selection and Bagging Ensemble Learning Methods

Figure 4

Receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) results of the generalized logistic regression analysis (GLRA), support vector machine (SVM), and Bagging ensemble input with the MKLD and ICPR selected features, respectively. GLRA-MKLD AUC standard error (SE): ; GLRA-ICPR AUC SE: ; SVM-MKLD AUC SE: 0.9216  ±  0.023; SVM-ICPR AUC SE: ; Bagging-MKLD AUC SE: , Bagging-ICPR AUC SE: .