Model performance measures for the indicated outcomes using a random forest algorithm.</p
(A) Decision trees use tree representations to solve problems, in which leaves represent class label...
Random forest classification results for the whole dataset with stratified k-fold and oversampling.<...
<p>Classification performance measures of final prediction model at different risk thresholds.</p
Performance metrics of the final prediction model on the test set using the random forest method.</p
Performance indicators for variable forecasting based only in the most important variables using ran...
Performance metrics of the prediction models using logistic regression and random forest methods wit...
<p>Performance of the KNN and random forest classification models for determination of cancer type.<...
The plot shows the predictive performances for the different methods when normalized data were class...
<p>Performance of the random forest classifier for the positive class in 10-fold cross-validation.</...
Models for each individual state created using random forests analysis with explanatory variables li...
<p>Performance of random forest model for cocaine and saline treatment measured by 5-fold cross vali...
Performance of two random forest models on validation set of 152 FDA-approved drugs as a function of...
<p>Accuracies of random forest models built on different HMs and combination of HMs.</p
Performance statistics of the tested algorithms at different activity levels.</p
<p>The metric in mean (standard deviation) of 10 iterations on 15-fold cross-validation test for the...
(A) Decision trees use tree representations to solve problems, in which leaves represent class label...
Random forest classification results for the whole dataset with stratified k-fold and oversampling.<...
<p>Classification performance measures of final prediction model at different risk thresholds.</p
Performance metrics of the final prediction model on the test set using the random forest method.</p
Performance indicators for variable forecasting based only in the most important variables using ran...
Performance metrics of the prediction models using logistic regression and random forest methods wit...
<p>Performance of the KNN and random forest classification models for determination of cancer type.<...
The plot shows the predictive performances for the different methods when normalized data were class...
<p>Performance of the random forest classifier for the positive class in 10-fold cross-validation.</...
Models for each individual state created using random forests analysis with explanatory variables li...
<p>Performance of random forest model for cocaine and saline treatment measured by 5-fold cross vali...
Performance of two random forest models on validation set of 152 FDA-approved drugs as a function of...
<p>Accuracies of random forest models built on different HMs and combination of HMs.</p
Performance statistics of the tested algorithms at different activity levels.</p
<p>The metric in mean (standard deviation) of 10 iterations on 15-fold cross-validation test for the...
(A) Decision trees use tree representations to solve problems, in which leaves represent class label...
Random forest classification results for the whole dataset with stratified k-fold and oversampling.<...
<p>Classification performance measures of final prediction model at different risk thresholds.</p
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