Sample: 41
ID: X00016469670
Recall: 78.72%
Precision: 78.26%
Hmean: 78.49%
Sample: 42
ID: X00016469671
Recall: 46.34%
Precision: 47.50%
Hmean: 46.91%
Sample: 43
ID: X51005200931
Recall: 65.19%
Precision: 64.58%
Hmean: 64.88%
Sample: 44
ID: X51005230605
Recall: 52.27%
Precision: 52.63%
Hmean: 52.45%
Sample: 45
ID: X51005230616
Recall: 82.61%
Precision: 82.61%
Hmean: 82.61%
Sample: 46
ID: X51005230621
Recall: 90.74%
Precision: 96.00%
Hmean: 93.30%
Sample: 47
ID: X51005230648
Recall: 95.56%
Precision: 95.24%
Hmean: 95.40%
Sample: 48
ID: X51005230657
Recall: 92.63%
Precision: 99.18%
Hmean: 95.80%
Sample: 49
ID: X51005230659
Recall: 100.00%
Precision: 100.00%
Hmean: 100.00%
Sample: 50
ID: X51005268275
Recall: 72.81%
Precision: 84.05%
Hmean: 78.03%
Sample: 51
ID: X51005268408
Recall: 94.74%
Hmean: 97.30%
Sample: 52
ID: X51005288570
Sample: 53
ID: X51005301666
Sample: 54
ID: X51005337867
Recall: 80.33%
Precision: 95.45%
Hmean: 87.24%
Sample: 55
ID: X51005337877
Sample: 56
ID: X51005361906
Recall: 77.78%
Precision: 94.03%
Hmean: 85.14%
Sample: 57
ID: X51005361908
Recall: 88.52%
Precision: 96.43%
Hmean: 92.31%
Sample: 58
ID: X51005361912
Recall: 83.87%
Precision: 98.11%
Hmean: 90.43%
Sample: 59
ID: X51005361923
Sample: 60
ID: X51005365187
Recall: 93.40%
Precision: 98.97%
Hmean: 96.10%