Sample: 1
ID: X00016469670
Recall: 93.62%
Precision: 93.48%
Hmean: 93.55%
Sample: 2
ID: X00016469671
Recall: 65.85%
Precision: 65.85%
Hmean: 65.85%
Sample: 3
ID: X51005200931
Recall: 73.83%
Precision: 78.70%
Hmean: 76.19%
Sample: 4
ID: X51005230605
Recall: 47.27%
Precision: 48.00%
Hmean: 47.63%
Sample: 5
ID: X51005230616
Recall: 80.00%
Precision: 76.73%
Hmean: 78.33%
Sample: 6
ID: X51005230621
Recall: 94.44%
Precision: 100.00%
Hmean: 97.14%
Sample: 7
ID: X51005230648
Recall: 100.00%
Hmean: 100.00%
Sample: 8
ID: X51005230657
Recall: 92.63%
Precision: 97.31%
Hmean: 94.91%
Sample: 9
ID: X51005230659
Sample: 10
ID: X51005268275
Recall: 99.33%
Precision: 98.48%
Hmean: 98.90%
Sample: 11
ID: X51005268408
Recall: 97.37%
Hmean: 98.67%
Sample: 12
ID: X51005288570
Sample: 13
ID: X51005301666
Recall: 96.18%
Precision: 95.65%
Hmean: 95.92%
Sample: 14
ID: X51005337867
Recall: 96.72%
Precision: 98.28%
Hmean: 97.49%
Sample: 15
ID: X51005337877
Sample: 16
ID: X51005361906
Recall: 81.48%
Hmean: 88.00%
Sample: 17
ID: X51005361908
Recall: 84.92%
Precision: 97.41%
Hmean: 90.73%
Sample: 18
ID: X51005361912
Recall: 94.84%
Precision: 97.70%
Hmean: 96.25%
Sample: 19
ID: X51005361923
Recall: 93.94%
Hmean: 96.88%
Sample: 20
ID: X51005365187