Skip to main content

Table 2 The comparison between our model and other methods under tenfold cross-validations on the HMDAD database

From: Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

Method

AUROC

AUPR

F1

Precision

Recall

Accuracy

MVGAEW

0.9798

0.9855

0.9412

0.9524

0.9302

0.9444

GATMDA

0.9398

0.9364

0.8151

0.8672

0.7689

0.8256

RNMFMDA

0.9124

0.2767

0.1297

0.0753

0.4667

0.9732

KATZHMDA

0.8348

0.5910

0.2017

0.1160

0.7733

0.7482

LRLSHMDA

0.8851

0.6080

0.2243

0.1290

0.8600

0.7553

MVGCNMDA

0.9196

0.9237

0.9113

0.9843

0.8484

0.9178

MVFA

0.9718

0.8864

0.8755

0.7961

0.9729

0.8622

  1. The bold values denote the max value in columns
Back to article page

BMC Biology

ISSN: 1741-7007

Contact us