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Table 2 Statistical results for the QSAR models based on 120 descriptors and Pubchem 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

\(q_{ext}^{2}\)

RMSEtrain

MAEtrain

RMSEtest

MAEtest

AD coverage (%)

kNN

0.783

0.774

0.602

0.413

0.299

0.707

0.398

51.4

RF

0.949

0.922

0.639

0.242

0.171

0.707

0.544

81.7

SVM

0.923

0.915

0.627

0.253

0.119

0.688

0.507

58.6

RVM

0.936

0.935

0.644

0.221

0.172

0.680

0.511

62.9

laGP

0.775

0.756

0.614

0.430

0.322

0.713

0.550

72.2

MPLE

0.716

0.693

0.580

0.482

0.349

0.743

0.572

78.4

XGBoost

0.920

0.903

0.624

0.271

0.205

0.700

0.533

74.5

Consensus

0.923

NA

0.676

0.278

0.208

0.666

0.504

71.7

Consensus (Except MPLE)

0.933

NA

0.678

0.257

0.194

0.661

0.499

68.9