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Table 4 Statistical results for the QSAR models based on 120 descriptors and Substructural fingerprints for the test set

From: ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling

 

R 2adj

q 2

\(\varvec{q}_{{\varvec{ext}}}^{2}\)

RMSEtrain

MAEtrain

RMSEtest

MAEtest

AD coverage (%)

kNN

0.815

0.805

0.636

0.383

0.277

0.674

0.364

46.1

RF

0.942

0.914

0.645

0.239

0.172

0.691

0.525

76.2

SVM

0.681

0.668

0.617

0.501

0.323

0.701

0.516

63.3

RVM

0.934

0.933

0.655

0.224

0.172

0.662

0.498

56.4

laGP

0.767

0.745

0.634

0.438

0.328

0.693

0.530

71.1

MPLE

0.679

0.656

0.596

0.509

0.374

0.729

0.558

77.0

XGBoost

0.920

0.902

0.644

0.272

0.205

0.681

0.516

67.7

Consensus

0.888

NA

0.687

0.330

0.249

0.654

0.495

69.9

Consensus (Except MPLE)

0.897

NA

0.689

0.314

0.237

0.652

0.493

68.5