Sample: 1
ID: X00016469670
Recall: 91.49%
Precision: 95.45%
Hmean: 93.43%
Sample: 2
ID: X00016469671
Recall: 92.68%
Precision: 90.48%
Hmean: 91.57%
Sample: 3
ID: X51005200931
Recall: 80.25%
Precision: 73.86%
Hmean: 76.92%
Sample: 4
ID: X51005230605
Recall: 76.82%
Precision: 80.00%
Hmean: 78.38%
Sample: 5
ID: X51005230616
Recall: 91.30%
Precision: 89.36%
Hmean: 90.32%
Sample: 6
ID: X51005230621
Recall: 94.44%
Precision: 98.08%
Hmean: 96.23%
Sample: 7
ID: X51005230648
Recall: 100.00%
Precision: 100.00%
Hmean: 100.00%
Sample: 8
ID: X51005230657
Recall: 96.14%
Precision: 99.22%
Hmean: 97.65%
Sample: 9
ID: X51005230659
Sample: 10
ID: X51005268275
Recall: 88.99%
Precision: 97.08%
Hmean: 92.86%
Sample: 11
ID: X51005268408
Recall: 97.37%
Hmean: 98.67%
Sample: 12
ID: X51005288570
Sample: 13
ID: X51005301666
Recall: 87.87%
Precision: 95.96%
Hmean: 91.73%
Sample: 14
ID: X51005337867
Recall: 98.36%
Precision: 95.00%
Hmean: 96.65%
Sample: 15
ID: X51005337877
Recall: 96.23%
Hmean: 97.14%
Sample: 16
ID: X51005361906
Recall: 89.88%
Precision: 96.84%
Hmean: 93.23%
Sample: 17
ID: X51005361908
Recall: 90.16%
Precision: 98.18%
Hmean: 94.00%
Sample: 18
ID: X51005361912
Recall: 88.71%
Precision: 98.21%
Hmean: 93.22%
Sample: 19
ID: X51005361923
Sample: 20
ID: X51005365187