Sample: 1
ID: X00016469670
Recall: 97.87%
Precision: 100.00%
Hmean: 98.92%
Sample: 2
ID: X00016469671
Recall: 97.07%
Precision: 99.02%
Hmean: 98.04%
Sample: 3
ID: X51005200931
Recall: 85.93%
Precision: 98.89%
Hmean: 91.95%
Sample: 4
ID: X51005230605
Recall: 93.18%
Hmean: 96.47%
Sample: 5
ID: X51005230616
Recall: 93.04%
Precision: 99.09%
Hmean: 95.97%
Sample: 6
ID: X51005230621
Recall: 100.00%
Hmean: 100.00%
Sample: 7
ID: X51005230648
Sample: 8
ID: X51005230657
Recall: 90.88%
Precision: 99.15%
Hmean: 94.83%
Sample: 9
ID: X51005230659
Sample: 10
ID: X51005268275
Recall: 98.65%
Precision: 99.47%
Hmean: 99.06%
Sample: 11
ID: X51005268408
Sample: 12
ID: X51005288570
Sample: 13
ID: X51005301666
Recall: 97.30%
Precision: 98.95%
Hmean: 98.12%
Sample: 14
ID: X51005337867
Recall: 99.67%
Precision: 99.32%
Hmean: 99.50%
Sample: 15
ID: X51005337877
Sample: 16
ID: X51005361906
Recall: 96.05%
Precision: 99.49%
Hmean: 97.74%
Sample: 17
ID: X51005361908
Recall: 90.16%
Sample: 18
ID: X51005361912
Recall: 98.39%
Hmean: 99.19%
Sample: 19
ID: X51005361923
Recall: 96.97%
Hmean: 98.46%
Sample: 20
ID: X51005365187