Table 1 Accuracy of proposed model and predictors trained with full ClinVar version 2017-05-30, according to ClinVar version 2019-09-23
From: A decision tree to improve identification of pathogenic mutations in clinical practice
Classifier | Accuracy *Mean (± Std. Dev.) | Predictor = N, Clinvar = 0 *Mean (± Std. Dev.) | Predictor = P, Clinvar = 0 *Mean (± Std. Dev.) | Predictor = N, Clinvar = 1 *Mean (± Std. Dev.) | Predictor = P, Clinvar = 1 *Mean (± Std. Dev.) |
|---|---|---|---|---|---|
Extreme Gradient Boosting | 93 (0.3) | 92 (0.5) | 8 (0.5) | 7 (0.3) | 93 (0.3) |
* Proposed Tree | 92 (0.3) | 91 (0.5) | 9 (0.5) | 8 (0.3) | 92 (0.3) |
Random Forest | 92 (0.3) | 91 (0.5) | 9 (0.5) | 8 (0.3) | 92 (0.3) |
Bagging | 92 (0.3) | 90 (0.5) | 10 (0.5) | 8 (0.3) | 92 (0.3) |
K Nearest Neighbors | 92 (0.3) | 89 (0.5) | 11 (0.5) | 6 (0.3) | 94 (0.3) |
Ada Boost | 92 (0.3) | 93 (0.5) | 7 (0.5) | 8 (0.3) | 92 (0.3) |
Extra Trees | 91 (0.3) | 90 (0.5) | 10 (0.5) | 8 (0.3) | 92 (0.3) |
Extra Tree | 91 (0.3) | 90 (0.5) | 10 (0.5) | 8 (0.3) | 92 (0.3) |
Linear Discriminant Analysis | 91 (0.3) | 88 (0.6) | 12 (0.6) | 8 (0.3) | 92 (0.3) |
Support Vector Machines (Linear kernel) | 91 (0.3) | 86 (0.6) | 14 (0.6) | 6 (0.3) | 94 (0.3) |
SKLearn Decision Tree | 91 (0.3) | 90 (0.5) | 10 (0.5) | 8 (0.3) | 92 (0.3) |
Multilayer Perceptron | 91 (0.3) | 85 (0.6) | 15 (0.6) | 6 (0.3) | 94 (0.3) |
Quadratic Discriminant Analysis | 91 (0.3) | 88 (0.5) | 12 (0.5) | 8 (0.3) | 92 (0.3) |
Bernoulli Naive Bayes | 91 (0.3) | 86 (0.6) | 14 (0.6) | 7 (0.3) | 93 (0.3) |
Support Vector Machines (RBF Kernel) | 91 (0.3) | 86 (0.6) | 14 (0.6) | 7 (0.3) | 93 (0.3) |
Logistic Regression | 91 (0.3) | 86 (0.6) | 14 (0.6) | 7 (0.3) | 93 (0.3) |
Gaussian Naive Bayes | 90 (0.3) | 84 (0.6) | 16 (0.6) | 6 (0.3) | 94 (0.3) |
Nu-Support Vector Machines | 87 (0.4) | 82 (0.6) | 18 (0.6) | 11 (0.3) | 89 (0.3) |
PROVEAN | 83 (0.4) | 75 (0.7) | 25 (0.7) | 13 (0.4) | 87 (0.4) |
MetaSVM | 81 (0.4) | 69 (0.6) | 31 (0.6) | 10 (0.4) | 90 (0.4) |
Polyphen | 80 (0.4) | 82 (0.8) | 18 (0.8) | 20 (0.3) | 80 (0.3) |
SIFT | 80 (0.4) | 77 (0.8) | 23 (0.8) | 18 (0.4) | 82 (0.4) |