Sample: 1
ID: 000001
Recall: 80.00%
Precision: 80.00%
Hmean: 80.00%
1-NED: 66.67%
Sample: 2
ID: 000002
Recall: 85.71%
Precision: 100.00%
Hmean: 92.31%
1-NED: 71.43%
Sample: 3
ID: 000003
Recall: 83.33%
Hmean: 90.91%
1-NED: 74.44%
Sample: 4
ID: 000004
Recall: 100.00%
Hmean: 100.00%
1-NED: 88.89%
Sample: 5
ID: 000005
Precision: 85.71%
Hmean: 85.71%
1-NED: 40.63%
Sample: 6
ID: 000006
Recall: 84.62%
Precision: 91.67%
Hmean: 88.00%
1-NED: 65.27%
Sample: 7
ID: 000007
Precision: 93.75%
Hmean: 96.77%
1-NED: 71.67%
Sample: 8
ID: 000008
1-NED: 100.00%
Sample: 9
ID: 000009
Precision: 87.50%
Hmean: 93.33%
1-NED: 60.42%
Sample: 10
ID: 000010
Sample: 11
ID: 000011
1-NED: 76.67%
Sample: 12
ID: 000012
Sample: 13
ID: 000013
1-NED: 75.00%
Sample: 14
ID: 000014
Precision: 66.67%
Hmean: 75.00%
1-NED: 54.17%
Sample: 15
ID: 000015
Recall: 50.00%
Hmean: 66.67%
1-NED: 25.00%
Sample: 16
ID: 000016
Hmean: 88.89%
1-NED: 34.00%
Sample: 17
ID: 000017
1-NED: 50.00%
Sample: 18
ID: 000018
Recall: 63.64%
Hmean: 77.78%
1-NED: 41.01%
Sample: 19
ID: 000019
1-NED: 84.26%
Sample: 20
ID: 000020
Hmean: 82.76%
1-NED: 57.06%