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Table 3 The efficiency analysis under different level of noise interference by using the simulated data who’s best performance showed at a threshold on 0 L d( O m , O c , O t ) 0.8 and D(O m , O c , O t ) < 0.8

From: Inferring microbial interaction network from microbiome data using RMN algorithm

Non-noise Accuracy TPR TNR F-measure
L0.8D0.8 0.861 0.929 0.855 0.890
L1.8D0.8 0.706 1.000 0.681 0.810
L2.8D0.8 0.617 1.000 0.584 0.738
L3.8D0.8 0.556 1.000 0.518 0.683
L0.8D1.8 0.828 0.929 0.819 0.871
L0.8D2.8 0.828 0.929 0.819 0.871
L0.8D3.8 0.828 0.929 0.819 0.871
Low-noise Accuracy TPR TNR F-measure
L0.8D0.8 0.856 0.929 0.849 0.887
L1.8D0.8 0.678 0.929 0.657 0.769
L2.8D0.8 0.611 0.929 0.584 0.717
L3.8D0.8 0.550 0.929 0.518 0.665
L0.8D1.8 0.761 0.929 0.747 0.828
L0.8D2.8 0.761 0.929 0.747 0.828
L0.8D3.8 0.761 0.929 0.747 0.828
Medium-noise Accuracy TPR TNR F-measure
L0.8D0.8 0.828 0.857 0.825 0.841
L1.8D0.8 0.706 0.929 0.687 0.790
L2.8D0.8 0.622 0.929 0.596 0.726
L3.8D0.8 0.533 0.929 0.500 0.650
L0.8D1.8 0.744 0.857 0.735 0.791
L0.8D2.8 0.744 0.857 0.735 0.791
L0.8D3.8 0.744 0.857 0.735 0.791
High-noise Accuracy TPR TNR F-measure
L0.8D0.8 0.850 0.857 0.849 0.853
L1.8D0.8 0.733 0.929 0.717 0.809
L2.8D0.8 0.633 0.929 0.608 0.735
L3.8D0.8 0.572 0.929 0.542 0.685
L0.8D1.8 0.778 0.857 0.771 0.812
L0.8D2.8 0.778 0.857 0.771 0.812
L0.8D3.8 0.778 0.857 0.771 0.812