Performance of machine learning models on test set using the SMOTE-adjusted balanced training set.</p
<p>The performance comparison of the models trained with different sequence lengths.</p
The average accuracy, AUPRC, and MCC of the supervised learning models for the external dataset.</p
<p>Performance of the models trained by human polymorphism and primate polymorphism.</p
Performance of machine learning models on test set using the ROSE-adjusted balanced training set.</p
Performance of machine learning models on test set using the original imbalanced training set.</p
Performance of the machine-learned model when propensity matching based on age and gender.</p
The evaluation results based on four simple machine learning models for two datasets.</p
Performance of the machine learning algorithms for survivability predictions.</p
<p>Test set performance of the ML models for 20-class document classification.</p
Performance comparison of the machine learning models regarding the use of KNN imputer.</p
The 95% confidence intervals of accuracy and MCC of the supervised learning models for the main data...
The average accuracy, AUPRC, and MCC of the supervised learning models for the main dataset.</p
Performance parameter values for five machine learning algorithms before and after over-sampling.</p
<p>The RTF model achieve the highest AUC (0.88), Sensitivity (74.30%), Precision (73.50%) and F-Scor...
<p>Average training (ten animals) and testing (two unseen animals) accuracy of machine learning mode...
<p>The performance comparison of the models trained with different sequence lengths.</p
The average accuracy, AUPRC, and MCC of the supervised learning models for the external dataset.</p
<p>Performance of the models trained by human polymorphism and primate polymorphism.</p
Performance of machine learning models on test set using the ROSE-adjusted balanced training set.</p
Performance of machine learning models on test set using the original imbalanced training set.</p
Performance of the machine-learned model when propensity matching based on age and gender.</p
The evaluation results based on four simple machine learning models for two datasets.</p
Performance of the machine learning algorithms for survivability predictions.</p
<p>Test set performance of the ML models for 20-class document classification.</p
Performance comparison of the machine learning models regarding the use of KNN imputer.</p
The 95% confidence intervals of accuracy and MCC of the supervised learning models for the main data...
The average accuracy, AUPRC, and MCC of the supervised learning models for the main dataset.</p
Performance parameter values for five machine learning algorithms before and after over-sampling.</p
<p>The RTF model achieve the highest AUC (0.88), Sensitivity (74.30%), Precision (73.50%) and F-Scor...
<p>Average training (ten animals) and testing (two unseen animals) accuracy of machine learning mode...
<p>The performance comparison of the models trained with different sequence lengths.</p
The average accuracy, AUPRC, and MCC of the supervised learning models for the external dataset.</p
<p>Performance of the models trained by human polymorphism and primate polymorphism.</p
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