Sample: 1
ID: X00016469670
Recall: 97.87%
Precision: 100.00%
Hmean: 98.92%
Sample: 2
ID: X00016469671
Recall: 97.56%
Precision: 97.50%
Hmean: 97.53%
Sample: 3
ID: X51005200931
Recall: 91.36%
Precision: 86.05%
Hmean: 88.62%
Sample: 4
ID: X51005230605
Recall: 90.00%
Precision: 89.57%
Hmean: 89.78%
Sample: 5
ID: X51005230616
Recall: 97.83%
Precision: 93.75%
Hmean: 95.74%
Sample: 6
ID: X51005230621
Recall: 98.15%
Precision: 98.15%
Hmean: 98.15%
Sample: 7
ID: X51005230648
Recall: 93.33%
Hmean: 96.55%
Sample: 8
ID: X51005230657
Recall: 96.49%
Hmean: 98.21%
Sample: 9
ID: X51005230659
Recall: 100.00%
Hmean: 100.00%
Sample: 10
ID: X51005268275
Recall: 97.98%
Precision: 97.47%
Hmean: 97.72%
Sample: 11
ID: X51005268408
Sample: 12
ID: X51005288570
Sample: 13
ID: X51005301666
Recall: 96.85%
Hmean: 97.16%
Sample: 14
ID: X51005337867
Recall: 98.36%
Precision: 98.25%
Hmean: 98.30%
Sample: 15
ID: X51005337877
Sample: 16
ID: X51005361906
Recall: 99.75%
Precision: 99.51%
Hmean: 99.63%
Sample: 17
ID: X51005361908
Precision: 98.33%
Hmean: 99.16%
Sample: 18
ID: X51005361912
Sample: 19
ID: X51005361923
Sample: 20
ID: X51005365187
Recall: 99.06%
Precision: 99.03%
Hmean: 99.04%