Research Article

Multifeature Metric Learning Based on Enhanced Equidistance Embedding for Electroencephalogram Recognition of Epilepsy

Table 2

Results of sensitivity rates (%) of MMLE3 and the comparison algorithms.

Patient IDLMNNITMLRDML-CCPVLEquiDMLMV-TSK-FSCMMLMvCVMMMLE3

192.7293.4693.6494.5295.8995.3295.2097.28
292.4093.0493.7394.7194.5895.4695.0397.13
390.7690.9891.1292.6792.9492.6192.8794.64
493.0593.9193.9895.0395.6696.1895.0297.28
592.6992.8492.8293.9894.9994.7293.9096.49
791.3291.7792.8092.8994.5594.2093.8595.95
893.5794.1194.0194.8295.9195.5094.6797.47
992.4492.6593.6694.5495.3595.4994.7596.81
1092.1891.6892.7093.7794.3594.2093.3595.94
1192.1091.8392.9893.5695.0194.2794.5096.23
1392.4192.3692.8793.9594.5394.6694.6096.43
1491.7692.4592.3693.6394.2394.6693.3896.00
1592.9592.1993.3594.2495.2294.8793.9096.51
1793.3492.8393.2794.5495.5095.4794.9196.95
1892.7893.3193.8894.0795.4995.1695.0897.01
1993.0793.5594.5495.3795.5096.2094.7397.44
2093.0093.4493.7094.0995.1294.9594.3196.99
2193.0293.1493.5794.9495.6695.0994.9996.96
2292.0992.9192.8593.6194.6894.5894.1696.52
2393.0192.4893.1094.0694.8294.7894.1896.85
2492.6592.9892.7693.4894.3894.9694.1696.56
Mean92.5492.7693.2294.1294.9794.9294.3696.64

The bold values mean that they are the best classification results in the experiments.