From: G4Boost: a machine learning-based tool for quadruplex identification and stability prediction
 | Accuracy | F1-score | Precision | Recall | AUROC | |||||
---|---|---|---|---|---|---|---|---|---|---|
Average | SD | Average | SD | Average | SD | Average | SD | Average | SD | |
XGBoost | 0.938 | 0.002 | 0.964 | 0.001 | 0.959 | 0.006 | 0.969 | 0.004 | 0.976 | 0.002 |
NeuralNet | 0.934 | 0.002 | 0.962 | 0.001 | 0.964 | 0.009 | 0.959 | 0.011 | 0.974 | 0.002 |
RandomForest | 0.933 | 0.003 | 0.961 | 0.002 | 0.956 | 0.006 | 0.966 | 0.003 | 0.963 | 0.005 |
KNN | 0.928 | 0.003 | 0.958 | 0.002 | 0.955 | 0.007 | 0.961 | 0.005 | 0.937 | 0.010 |
CART | 0.928 | 0.005 | 0.958 | 0.003 | 0.958 | 0.006 | 0.958 | 0.005 | 0.919 | 0.016 |
LR | 0.927 | 0.003 | 0.958 | 0.002 | 0.949 | 0.007 | 0.968 | 0.005 | 0.966 | 0.003 |
LDA | 0.907 | 0.005 | 0.947 | 0.003 | 0.932 | 0.004 | 0.962 | 0.004 | 0.941 | 0.005 |
NBayes | 0.790 | 0.019 | 0.862 | 0.014 | 0.990 | 0.005 | 0.764 | 0.022 | 0.943 | 0.015 |