Sample: 1
ID: X00016469670
Recall: 100.00%
Precision: 100.00%
Hmean: 100.00%
Sample: 2
ID: X00016469671
Recall: 95.12%
Precision: 95.12%
Hmean: 95.12%
Sample: 3
ID: X51005200931
Recall: 90.12%
Precision: 89.02%
Hmean: 89.57%
Sample: 4
ID: X51005230605
Recall: 72.27%
Precision: 72.44%
Hmean: 72.36%
Sample: 5
ID: X51005230616
Recall: 89.13%
Precision: 85.42%
Hmean: 87.23%
Sample: 6
ID: X51005230621
Recall: 92.59%
Precision: 92.59%
Hmean: 92.59%
Sample: 7
ID: X51005230648
Sample: 8
ID: X51005230657
Recall: 94.39%
Precision: 95.47%
Hmean: 94.93%
Sample: 9
ID: X51005230659
Recall: 97.22%
Precision: 97.14%
Hmean: 97.18%
Sample: 10
ID: X51005268275
Recall: 87.87%
Precision: 89.33%
Hmean: 88.59%
Sample: 11
ID: X51005268408
Sample: 12
ID: X51005288570
Sample: 13
ID: X51005301666
Recall: 92.36%
Precision: 94.89%
Hmean: 93.61%
Sample: 14
ID: X51005337867
Recall: 93.44%
Precision: 93.10%
Hmean: 93.27%
Sample: 15
ID: X51005337877
Recall: 98.11%
Precision: 97.96%
Hmean: 98.04%
Sample: 16
ID: X51005361906
Precision: 93.75%
Hmean: 93.17%
Sample: 17
ID: X51005361908
Recall: 94.75%
Precision: 94.52%
Hmean: 94.63%
Sample: 18
ID: X51005361912
Recall: 88.71%
Precision: 88.71%
Hmean: 88.71%
Sample: 19
ID: X51005361923
Sample: 20
ID: X51005365187
Recall: 94.34%
Precision: 94.17%
Hmean: 94.26%