Table 1.

Performance comparison of seven machine-learning and deep-learning models for identifying leaf rust-responsive candidate genes

Model	Accuracy	Recall (TPR)	Specificity (TNR)	Precision (PPV)	Negative predictive value (NPV)	F1-score
Logistic Regression	0.70	0.75	0.63	0.75	0.63	0.75
Random Forest	0.80	0.92	0.63	0.79	0.83	0.85
Gradient Boosting	0.85	0.92	0.75	0.85	0.86	0.88
SVM	0.60	0.58	0.63	0.70	0.50	0.64
LightGBM	0.80	0.92	0.63	0.79	0.83	0.85
XGBoost	0.90	1.00	0.75	0.86	1.00	0.92
Neural Network	0.70	0.83	0.50	0.71	0.67	0.77