Sample: 1
ID: X00016469670
Recall: 100.00%
Precision: 100.00%
Hmean: 100.00%
Sample: 2
ID: X00016469671
Recall: 99.51%
Precision: 99.05%
Hmean: 99.28%
Sample: 3
ID: X51005200931
Recall: 91.36%
Precision: 87.06%
Hmean: 89.16%
Sample: 4
ID: X51005230605
Recall: 90.45%
Precision: 96.59%
Hmean: 93.42%
Sample: 5
ID: X51005230616
Recall: 99.13%
Precision: 96.33%
Hmean: 97.71%
Sample: 6
ID: X51005230621
Precision: 96.43%
Hmean: 98.18%
Sample: 7
ID: X51005230648
Sample: 8
ID: X51005230657
Recall: 94.39%
Precision: 95.71%
Hmean: 95.05%
Sample: 9
ID: X51005230659
Sample: 10
ID: X51005268275
Recall: 88.76%
Precision: 89.25%
Hmean: 89.01%
Sample: 11
ID: X51005268408
Sample: 12
ID: X51005288570
Sample: 13
ID: X51005301666
Recall: 95.51%
Precision: 96.56%
Hmean: 96.03%
Sample: 14
ID: X51005337867
Recall: 88.20%
Precision: 88.36%
Hmean: 88.28%
Sample: 15
ID: X51005337877
Sample: 16
ID: X51005361906
Recall: 92.59%
Precision: 91.36%
Hmean: 91.97%
Sample: 17
ID: X51005361908
Recall: 96.72%
Precision: 93.65%
Hmean: 95.16%
Sample: 18
ID: X51005361912
Recall: 88.71%
Precision: 88.71%
Hmean: 88.71%
Sample: 19
ID: X51005361923
Recall: 99.39%
Precision: 98.82%
Hmean: 99.11%
Sample: 20
ID: X51005365187
Recall: 93.21%
Precision: 92.88%
Hmean: 93.05%