<p>Performance of the random forest classifier for the positive class in 10-fold cross-validation.</p
Random forest classification results for the whole dataset with stratified k-fold and oversampling.<...
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
<p>The table shows the cross-validation performance of our method on the labeled data points. The me...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
Performance metrics of the final prediction model on the test set using the random forest method.</p
Five-fold cross-validation results performed by random forest classifier combined with the proposed ...
Model performance measures for the indicated outcomes using a random forest algorithm.</p
<p>The Random Forest classifier correctly classifies almost 90% of liver and 76% of plasma samples.<...
Performance of Support Vector Machine, Random Forest, Multilayer perception, and XGBoost classifiers...
<p>The metric in mean (standard deviation) of 10 iterations on 15-fold cross-validation test for the...
Performance of Support Vector Machine, Random Forest, Multilayer perception, and XGBoost classifiers...
<p>Overall classification results of the Random Forest classifier using the severeness measure <i>S<...
Performance metrics of the prediction models using logistic regression and random forest methods wit...
<p>Performance of random forest model for cocaine and saline treatment measured by 5-fold cross vali...
Unlike other decision tree classifiers, Random Forest grows multiple trees which create a forest-lik...
Random forest classification results for the whole dataset with stratified k-fold and oversampling.<...
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
<p>The table shows the cross-validation performance of our method on the labeled data points. The me...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
Performance metrics of the final prediction model on the test set using the random forest method.</p
Five-fold cross-validation results performed by random forest classifier combined with the proposed ...
Model performance measures for the indicated outcomes using a random forest algorithm.</p
<p>The Random Forest classifier correctly classifies almost 90% of liver and 76% of plasma samples.<...
Performance of Support Vector Machine, Random Forest, Multilayer perception, and XGBoost classifiers...
<p>The metric in mean (standard deviation) of 10 iterations on 15-fold cross-validation test for the...
Performance of Support Vector Machine, Random Forest, Multilayer perception, and XGBoost classifiers...
<p>Overall classification results of the Random Forest classifier using the severeness measure <i>S<...
Performance metrics of the prediction models using logistic regression and random forest methods wit...
<p>Performance of random forest model for cocaine and saline treatment measured by 5-fold cross vali...
Unlike other decision tree classifiers, Random Forest grows multiple trees which create a forest-lik...
Random forest classification results for the whole dataset with stratified k-fold and oversampling.<...
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
<p>The table shows the cross-validation performance of our method on the labeled data points. The me...
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