Research Article

Multi-Instance Multilabel Learning with Weak-Label for Predicting Protein Function in Electricigens

Table 5

Comparison results (mean ± std.) of MIMLwel models with four state-of-the-art MIML methods with different weak-label ratios on the Shewanella loihica PV-4 dataset.

W.L.R.MethodsHL↓maF1↑miF1↑

20%MIMLwel0.013 ± 0.0020.009 ± 0.0080.145 ± 0.111
MIMLNN0.010 ± 0.0020.000 ± 0.0000.000 ± 0.000 ●
MIMLRBF0.011 ± 0.0030.001 ± 0.0010.001 ± 0.001 ●
MIMLSVM0.012 ± 0.0020.005 ± 0.0020.004 ± 0.002 ●
EnMIMLNN {metric}0.010 ± 0.0030.001 ± 0.0010.001 ± 0.001 ●

40%MIMLwel0.010 ± 0.0020.005 ± 0.0030.092 ± 0.039
MIMLNN0.010 ± 0.0020.000 ± 0.0000.000 ± 0.000 ●
MIMLRBF0.010 ± 0.0020.001 ± 0.0020.001 ± 0.002 ●
MIMLSVM0.012 ± 0.0020.004 ± 0.0020.004 ± 0.002 ●
EnMIMLNN {metric}0.010 ± 0.0020.001 ± 0.0030.001 ± 0.003 ●

60%MIMLwel0.011 ± 0.0030.010 ± 0.0060.167 ± 0.072
MIMLNN0.010 ± 0.0030.001 ± 0.0010.001 ± 0.001 ●
MIMLRBF0.010 ± 0.0040.004 ± 0.0040.003 ± 0.003 ●
MIMLSVM0.012 ± 0.0030.005 ± 0.0010.005 ± 0.002 ●
EnMIMLNN {metric}0.010 ± 0.0030.005 ± 0.0030.004 ± 0.003 ●

80%MIMLwel0.011 ± 0.0030.011 ± 0.0050.186 ± 0.043
MIMLNN0.010 ± 0.0030.002 ± 0.0010.001 ± 0.001 ●
MIMLRBF0.009 ± 0.0030.008 ± 0.0050.007 ± 0.005 ●
MIMLSVM0.012 ± 0.0030.005 ± 0.0020.005 ± 0.001 ●
EnMIMLNN {metric}0.010 ± 0.0030.006 ± 0.0040.005 ± 0.003 ●