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Table 6 Best testing results over 30 runs using the proposed AMSKF feature selection algorithm on eye event-related EEG data

From: Feature selection using angle modulated simulated Kalman filter for peak classification of EEG signals

Run Training (%) Validation (%) Testing (%) Best peak model               Feature subset length
1 87.52 63.88 69.19 1 3 4 6 7 8 9 10 11 12 13 14 15 16 14
2 90.14 63.92 62.89 1 2 3 4 5 6 7 8 9 15 16     11
3 95.12 61.30 55.78 1 2 3 4 5 6 7 8 9 10 11 16    12
4 91.77 61.68 72.71 1 2 7 8 9 10 11 12 13 14 15     11
5 78.33 65.99 56.51 13 14 15 16            4
6 89.44 71.36 62.21 3 6 7             3
7 93.81 67.50 66.78 1 2 8 9 10 11 12 13 14 15 16     11
8 96.61 67.19 60.02 1 5 9 13            4
9 94.65 64.64 66.50 1 2 14 15            4
10 92.20 60.68 57.87 2 3 8 9 10 13 14         7
11 95.74 66.54 62.55 1 11 12 15            4
12 82.57 65.36 61.47 12 13 14 15 16           5
13 92.20 71.06 64.64 1 2 5 13 14 15 16         7
14 91.50 71.13 59.16 3 6 14             3
15 89.44 58.06 60.60 1 2 3 7 8 10 11 13 15 16      10
16 88.19 65.65 60.32 1 2 5 6 7 8 9 10 13 14 15 16    12
17 90.83 70.24 55.20 1 2              2
18 86.92 67.34 60.51 1 2 5 6 7 8 9 10 13 14 15     11
19 95.24 62.63 61.98 1 2 3 4            4
20 88.80 68.93 66.51 1 2 3 15 16           5
21 85.54 66.92 61.66 9 10 11 12 13 14 15 16        8
22 94.15 66.02 57.85 1 3 4 7 9 11 14 16        8
23 82.12 62.33 61.34 12 13 14 15 16           5
24 95.59 65.14 62.30 1 2 3 9 10           5
25 83.67 68.40 62.37 1 2              2
26 92.08 66.54 61.75 3 9 15 16            4
27 80.18 63.01 61.96 14 15 16             3
28 94.15 66.95 52.96 1 10 11 12 13 14          6
29 87.60 60.47 63.47 12 13 14 15 16           5
30 89.92 71.94 62.34 3 4              2
  1. The best-generalized peak model based on the maximum accuracy of testing data over 30 runs was marked with the italic font