Sample: 1
ID: 000001
Recall: 80.00%
Precision: 80.00%
Hmean: 80.00%
1-NED: 66.67%
Sample: 2
ID: 000002
Recall: 83.33%
Precision: 100.00%
Hmean: 90.91%
1-NED: 16.11%
Sample: 3
ID: 000003
Recall: 66.67%
Precision: 66.67%
Hmean: 66.67%
1-NED: 45.83%
Sample: 4
ID: 000004
Recall: 100.00%
Hmean: 100.00%
1-NED: 100.00%
Sample: 5
ID: 000005
Recall: 33.33%
Hmean: 50.00%
1-NED: 26.67%
Sample: 6
ID: 000006
Recall: 77.78%
Precision: 70.00%
Hmean: 73.68%
1-NED: 55.56%
Sample: 7
ID: 000007
Recall: 69.23%
Precision: 90.00%
Hmean: 78.26%
1-NED: 0.00%
Sample: 8
ID: 000008
1-NED: 60.00%
Sample: 9
ID: 000009
Recall: 57.14%
Hmean: 61.54%
1-NED: 35.71%
Sample: 10
ID: 000010
Recall: 50.00%
Precision: 50.00%
1-NED: 33.33%
Sample: 11
ID: 000011
Hmean: 88.89%
1-NED: 60.91%
Sample: 12
ID: 000012
Sample: 13
ID: 000013
1-NED: 50.00%
Sample: 14
ID: 000014
Sample: 15
ID: 000015
Sample: 16
ID: 000016
Recall: 25.00%
Precision: 25.00%
Hmean: 25.00%
Sample: 17
ID: 000017
1-NED: 83.33%
Sample: 18
ID: 000018
Recall: 81.82%
Hmean: 90.00%
1-NED: 7.34%
Sample: 19
ID: 000019
1-NED: 22.50%
Sample: 20
ID: 000020
Recall: 93.33%
Precision: 87.50%
Hmean: 90.32%
1-NED: 40.00%