Table 2.
Wavelet basis § | Best feature combination | Sensitivity * (%) | Specificity † (%) | Classification rate ‡ (%) | ||
---|---|---|---|---|---|---|
Haar |
M-h1 |
M-d1 |
S-h3 |
99.2 |
36.6 |
60.3 |
Db 2 |
M-h3 |
M-d8 |
S-h5 |
97.4 |
42.7 |
63.4 |
Db 4 |
M-h8 |
M-d1 |
S-h5 |
95.2 |
20.8 |
49 |
Db 8 |
M-h6 |
S-v8 |
S-d3 |
97.5 |
40.4 |
62 |
Bior 1.5 |
M-d4 |
S-h6 |
--- |
96.9 |
38.8 |
60.8 |
Bior 2.2 |
M-h5 |
M-v2 |
S-d2 |
98.8 |
44.8 |
65.2 |
Bior 2.8 |
M-d4 |
S-d2 |
S-a5 |
92.9 |
46.9 |
64.4 |
Bior 3.7 |
M-d4 |
S-h4 |
S-d4 |
98.9 |
28.1 |
54.9 |
Bior 4.4 |
M-h1 |
M-d4 |
S-d2 |
96.1 |
43 |
63.1 |
Bior 5.5 |
M-h6 |
M-d5 |
S-d2 |
98.5 |
38.1 |
61 |
Bior 6.8 | M-v3 | M-d4 | S-d2 | 98 | 39 | 61.3 |
§Wavelet basis notation: Dbn where n describes the number of coefficients used in the wavelet. Db2 encodes polynomials with two coefficients, i.e. constant and linear components. Biorm.n where n describes the order for decomposition and m is the order used for reconstruction.
*Sensitivity is defined as TP/(TP + FN).
†Specificity is defined as TN/(TN + FP).
‡Classification rate is defined as (TP + TN)/(TP + TN + FP + FN).
The best triplet feature was selected for each wavelet.