Twin SVM-Based Classification of Alzheimer’s Disease Using Complex Dual-Tree Wavelet Principal Coefficients and LDA

Table 9

Classification performance of AD from HC over ADNI data.

Methods	Accuracy	Sensitivity	Specificity
Proposed	92.65 ± 1.18	93.11 ± 1.29	92.19 ± 1.56
DTCWT + PCA + TSVM	91.77 ± 0.85	92.48 ± 0.89	91.13 ± 1.31
DTCWT + PCA + LDA + Kernel SVM	90.181 ± 0.97	90.276 ± 1.60	90.101 ± 1.23
DTCWT + PCA + Kernel SVM	82.74 ± 1.24	84.43 ± 1.51	81.18 ± 1.85
DWT + PCA + LDA + TSVM	86.75 ± 1.69	89.32 ± 1.43	84.23 ± 2.21
DWT + PCA + TSVM	85.88 ± 1.16	88.93 ± 1.61	88.93 ± 2.02
DTCWT + PCA + LDA + ANN	86.97 ± 1.30	86.25 ± 1.78	87.72 ± 3.51
DTCWT + PCA + LDA + KNN	83.89 ± 0.75	81.41 ± 1.33	86.34 ± 1.08
DTCWT + PCA + LDA + AdaBoost (tree)	84.48	83.72	85.26
DWT + PCA + ANN [13]	80.05 ± 0.72	81.538 ± 1.41	78.974 ± 1.09
DWT + PCA + KNN [11]	79.964 ± 1.19	78.771 ± 2.37	81.08 ± 1.67
[24]	85	82	88