Sample: 1
ID: X00016469670
Recall: 95.74%
Precision: 95.65%
Hmean: 95.70%
Sample: 2
ID: X00016469671
Recall: 68.29%
Precision: 68.29%
Hmean: 68.29%
Sample: 3
ID: X51005200931
Recall: 81.23%
Precision: 75.68%
Hmean: 78.36%
Sample: 4
ID: X51005230605
Recall: 69.55%
Precision: 71.56%
Hmean: 70.54%
Sample: 5
ID: X51005230616
Recall: 93.48%
Precision: 87.76%
Hmean: 90.53%
Sample: 6
ID: X51005230621
Recall: 96.30%
Precision: 96.23%
Hmean: 96.26%
Sample: 7
ID: X51005230648
Recall: 100.00%
Precision: 100.00%
Hmean: 100.00%
Sample: 8
ID: X51005230657
Recall: 97.89%
Precision: 99.25%
Hmean: 98.57%
Sample: 9
ID: X51005230659
Sample: 10
ID: X51005268275
Recall: 92.36%
Precision: 95.11%
Hmean: 93.71%
Sample: 11
ID: X51005268408
Sample: 12
ID: X51005288570
Sample: 13
ID: X51005301666
Recall: 92.58%
Precision: 94.47%
Hmean: 93.52%
Sample: 14
ID: X51005337867
Recall: 98.03%
Precision: 96.00%
Hmean: 97.01%
Sample: 15
ID: X51005337877
Recall: 98.11%
Hmean: 99.05%
Sample: 16
ID: X51005361906
Recall: 96.05%
Precision: 99.49%
Hmean: 97.74%
Sample: 17
ID: X51005361908
Recall: 99.02%
Precision: 96.62%
Hmean: 97.80%
Sample: 18
ID: X51005361912
Recall: 92.90%
Precision: 95.48%
Hmean: 94.18%
Sample: 19
ID: X51005361923
Recall: 96.36%
Precision: 95.43%
Hmean: 95.89%
Sample: 20
ID: X51005365187