Sample: 1
ID: X00016469670
Recall: 85.59%
Precision: 78.51%
Hmean: 81.90%
Sample: 2
ID: X00016469671
Recall: 80.85%
Precision: 82.61%
Hmean: 81.72%
Sample: 3
ID: X51005200931
Recall: 68.00%
Precision: 69.39%
Hmean: 68.69%
Sample: 4
ID: X51005230605
Recall: 93.33%
Precision: 93.33%
Hmean: 93.33%
Sample: 5
ID: X51005230616
Recall: 87.88%
Precision: 86.57%
Hmean: 87.22%
Sample: 6
ID: X51005230621
Recall: 69.09%
Precision: 63.87%
Hmean: 66.38%
Sample: 7
ID: X51005230648
Recall: 85.19%
Precision: 83.64%
Hmean: 84.40%
Sample: 8
ID: X51005230657
Recall: 85.40%
Precision: 87.31%
Hmean: 86.35%
Sample: 9
ID: X51005230659
Recall: 81.48%
Precision: 85.71%
Hmean: 83.54%
Sample: 10
ID: X51005268275
Recall: 67.30%
Precision: 73.20%
Hmean: 70.12%
Sample: 11
ID: X51005268408
Recall: 57.84%
Precision: 57.84%
Hmean: 57.84%
Sample: 12
ID: X51005288570
Recall: 87.93%
Precision: 87.93%
Hmean: 87.93%
Sample: 13
ID: X51005301666
Recall: 68.57%
Precision: 74.23%
Hmean: 71.29%
Sample: 14
ID: X51005337867
Recall: 63.87%
Precision: 62.81%
Hmean: 63.33%
Sample: 15
ID: X51005337877
Recall: 94.17%
Precision: 91.51%
Hmean: 92.82%
Sample: 16
ID: X51005361906
Recall: 60.51%
Precision: 66.43%
Sample: 17
ID: X51005361908
Recall: 33.33%
Precision: 58.21%
Hmean: 42.39%
Sample: 18
ID: X51005361912
Recall: 67.80%
Precision: 75.47%
Hmean: 71.43%
Sample: 19
ID: X51005361923
Recall: 80.00%
Precision: 80.00%
Hmean: 80.00%
Sample: 20
ID: X51005365187
Recall: 80.84%
Precision: 79.41%
Hmean: 80.12%