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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