Brain Informatics

Table 2 k-NN classifier performance for alcoholic data

From: Pattern recognition of spectral entropy features for detection of alcoholic and control visual ERP’s in multichannel EEGs

No. of PC	No rank				Rank
No. of PC	Efficiency (%)	Sensitivity	Specificity	Time (s)	Efficiency (%)	Sensitivity	Specificity	Time (s)
N = 61
5	92.21	0.9461	0.7102	5.51	92.21	0.9461	0.7102	5.51
15	94.17	0.9620	0.7316	5.58	94.17	0.9620	0.7316	5.60
25	95.04	0.9820	0.7330	6.10	95.04	0.9820	0.7330	6.05
45	95.40	0.9878	0.7344	6.40	95.40	0.9878	0.7344	6.45
61	95.50	0.9881	0.7346	6.75	95.50	0.9881	0.7346	6.91
N = 25
5	84.42	0.8881	0.6463	5.44	91.01	0.9662	0.7194	5.42
15	90.92	0.9603	0.7144	5.68	93.42	0.9734	0.7451	5.68
25	91.54	0.9712	0.7232	5.9	93.87	0.9753	0.7480	5.90
N = 15
5	86.75	0.9091	0.6803	5.42	88.90	0.9201	0.7011	5.44
15	91.96	0.9763	0.7244	5.67	93.08	0.9701	0.7424	5.67

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