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Table 3 Accuracy metrics for antagonist activity evaluation with different numbers of activity sources per chemical

From: Exploring non-linear distance metrics in the structure–activity space: QSAR models for human estrogen receptor

# sources # chemicals Model and parameters Sensitivity Specificity Bal Accuracy Accuracy ROC AUC Score
1 6533 CERAPP consensus 0.15 0.91 0.53 0.88 0.55 0.26
1 6533 Morgan kNN arithm k = 3 0.04 0.99 0.52 0.95 0.53 0.26
1 6533 Morgan kNN geom k = 3 0.00 1.00 0.50 0.96 0.51 0.24
1 6533 Morgan kNN exp k = 3 X = 1.5 0.04 0.99 0.52 0.95 0.53 0.26
1 6533 Indigo kNN arithm k = 10 0.04 0.99 0.52 0.95 0.57 0.28
1 6533 Indigo kNN geom k = 10 0.00 1.00 0.50 0.96 0.50 0.24
1 6533 Indigo kNN exp k = 10 X = 1.5 0.05 0.99 0.52 0.95 0.57 0.28
1 6533 Indigo GkNN k = 10 X = 3 Y = 7 0.10 0.98 0.54 0.94 0.57 0.29
1 6533 Indigo GkNN k = 10 X = 5 Y = 15 0.10 0.98 0.54 0.94 0.57 0.29
3 1707 CERAPP consensus 0.17 0.90 0.53 0.87 0.58 0.27
3 1707 Morgan kNN arithm k = 3 0.09 0.99 0.54 0.95 0.57 0.29
3 1707 Morgan kNN geom k = 3 0.00 1.00 0.50 0.95 0.53 0.25
3 1707 Morgan kNN exp k = 3 X = 1.5 0.10 1.00 0.55 0.96 0.57 0.30
3 1707 Indigo kNN arithm k = 10 0.12 1.00 0.56 0.96 0.65 0.35
3 1707 Indigo kNN geom k = 10 0.00 1.00 0.50 0.95 0.50 0.24
3 1707 Indigo kNN exp k = 10 X = 1.5 0.14 1.00 0.57 0.96 0.65 0.36
3 1707 Indigo GkNN k = 10 X = 3 Y = 7 0.18 0.99 0.58 0.95 0.65 0.36
3 1707 Indigo GkNN k = 10 X = 5 Y = 15 0.18 0.99 0.58 0.95 0.65 0.36
5 431 CERAPP consensus 0.24 0.89 0.56 0.84 0.67 0.32
5 431 Morgan kNN arithm k = 3 0.14 0.99 0.56 0.93 0.61 0.32
5 431 Morgan kNN geom k = 3 0.00 1.00 0.50 0.93 0.52 0.24
5 431 Morgan kNN exp k = 3 X = 1.5 0.17 1.00 0.58 0.94 0.61 0.34
5 431 Indigo kNN arithm k = 10 0.10 1.00 0.55 0.94 0.65 0.33
5 431 Indigo kNN geom k = 10 0.00 1.00 0.50 0.93 0.50 0.23
5 431 Indigo kNN exp k = 10 X = 1.5 0.10 1.00 0.55 0.94 0.65 0.33
5 431 Indigo GkNN k = 10 X = 3 Y = 7 0.17 0.99 0.58 0.93 0.65 0.35
5 431 Indigo GkNN k = 10 X = 5 Y = 15 0.17 0.99 0.58 0.93 0.65 0.35
7 103 CERAPP consensus 0.31 0.91 0.61 0.84 0.67 0.34
7 103 Morgan kNN arithm k = 3 0.23 0.98 0.60 0.88 0.68 0.36
7 103 Morgan kNN geom k = 3 0.00 1.00 0.50 0.87 0.54 0.24
7 103 Morgan kNN exp k = 3 X = 1.5 0.23 1.00 0.62 0.90 0.68 0.38
7 103 Indigo kNN arithm k = 10 0.08 1.00 0.54 0.88 0.79 0.38
7 103 Indigo kNN geom k = 10 0.00 1.00 0.50 0.87 0.50 0.22
7 103 Indigo kNN exp k = 10 X = 1.5 0.15 0.98 0.57 0.87 0.80 0.39
7 103 Indigo GkNN k = 10 X = 3 Y = 7 0.23 0.98 0.60 0.88 0.80 0.43
7 103 Indigo GkNN k = 10 X = 5 Y = 15 0.31 0.99 0.65 0.90 0.80 0.47
9 46 CERAPP consensus 0.40 1.00 0.70 0.87 0.73 0.44
9 46 Morgan kNN arithm k = 3 0.30 0.97 0.64 0.83 0.73 0.38
9 46 Morgan kNN geom k = 3 0.00 1.00 0.50 0.78 0.55 0.22
9 46 Morgan kNN exp k = 3 X = 1.5 0.30 1.00 0.65 0.85 0.73 0.40
9 46 Indigo kNN arithm k = 10 0.10 1.00 0.55 0.80 0.79 0.35
9 46 Indigo kNN geom k = 10 0.00 1.00 0.50 0.78 0.50 0.20
9 46 Indigo kNN exp k = 10 X = 1.5 0.20 0.97 0.59 0.80 0.79 0.37
9 46 Indigo GkNN k = 10 X = 3 Y = 7 0.30 0.97 0.64 0.83 0.80 0.42
9 46 Indigo GkNN k = 10 X = 5 Y = 15 0.40 1.00 0.70 0.87 0.80 0.49
  1. “kNN arithm”, “kNN geom”, and “kNN exp” indicate the kNN models with the arithmetic, geometric, and exponential averaging, respectively. The cumulative score shown in the last column is the product of balanced accuracy, accuracy, and ROC AUC. Italic font indicates accuracy metric values that exceed those for the CERAPP consensus model