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Table 4 Validity and efficiency for active and inactive compounds at the 80% confidence level for the derived conformal predictors based on physicochemical descriptors

From: Maximizing gain in high-throughput screening using conformal prediction

AID

Validity active

Efficiency active

Validity inactive

Efficiency inactive

411 train

0.856

0.809

0.815

0.771

411 test

0.873

0.847

0.811

0.794

868 train

0.828

0.798

0.813

0.835

868 test

0.825

0.844

0.805

0.862

1030 train

0.823

0.654

0.819

0.636

1030 test

0.832

0.677

0.807

0.653

1460 train

0.864

0.864

0.816

0.88

1460 test

0.748

0.944

0.805

0.957

1721 train

0.868

0.918

0.842

0.899

1721 test

0.869

0.933

0.835

0.907

2314 train

0.813

0.81

0.807

0.808

2314 test

0.801

0.833

0.803

0.819

2326 train

1

0.395

0.856

0.144

2326 test

1

0.511

0.849

0.151

2451 train

0.884

0.746

0.836

0.66

2451 test

0.859

0.778

0.828

0.707

2551 train

0.819

0.916

0.809

0.906

2551 test

0.812

0.944

0.803

0.934

485290 train

1

0.51

0.86

0.15

485290 test

1

0.545

0.863

0.137

485314 train

0.846

0.762

0.824

0.726

485314 test

0.856

0.799

0.818

0.743

504444 train

0.833

0.749

0.813

0.755

504444 test

0.818

0.767

0.811

0.771

  1. Train denotes the results from the internal validation and test when the models are applied to the external test set