Development of a depression in Parkinson's disease prediction model using machine learning

Table 2 Comparing the accuracy of depression in Parkinson's disease prediction model, %

Type of algorithm	Overall accuracy	Sensitivity	Specificity
C-SVM: Linear	92.5	92.0	93.3
C-SVM: Polynomial	70.0	100	20.0
C-SVM: Gaussian	87.5	96.0	73.3
C-SVM: Sigmoid	85.0	88.0	80.0
Nu-SVM: Linear	90.0	92.0	86.6
Nu-SVM: Polynomial	92.5	92.0	93.3
Nu-SVM: Gaussian	95.0	96.0	93.3
Nu-SVM: Sigmoid	82.5	92.0	66.6

SVM: Support vector machine.