Predicted response versus true response of the trained optimizable ensemble of tree model.</p
The use of prediction error to optimize the number of splitting rules in a tree model does not contr...
<p>Prediction results of the original feature set and the optimal feature set.</p
Performance of machine learning models on test set using the ROSE-adjusted balanced training set.</p
Predicted response versus true response of the trained optimizable tree model.</p
<p>Comparison of the predictive power of tree-based methods and linear models.</p
Prediction metrics on held out data for the best performing gradient boosted decision trees model.</...
<p>A comparison of the performance of different tree inference methods following trimming of realign...
Model performance measures for the indicated outcomes using a random forest algorithm.</p
Performance metrics of the final prediction model on the test set using the random forest method.</p
<p>Observed versus predicted compressive strength produced by the SVM model (Training dataset).</p
<p>Diagnostic performance of a decision tree model with both training and validation datasets.</p
Response tree for the multivariable regression model for history of PrEP use.</p
Model predictions of response times by word gender and IAT pair in experiment 3.</p
Results of optimized parameter of the HKELM in the stage of ensemble learning.</p
Comparison of the performance of optimal experimental designs in supporting parameter inference for ...
The use of prediction error to optimize the number of splitting rules in a tree model does not contr...
<p>Prediction results of the original feature set and the optimal feature set.</p
Performance of machine learning models on test set using the ROSE-adjusted balanced training set.</p
Predicted response versus true response of the trained optimizable tree model.</p
<p>Comparison of the predictive power of tree-based methods and linear models.</p
Prediction metrics on held out data for the best performing gradient boosted decision trees model.</...
<p>A comparison of the performance of different tree inference methods following trimming of realign...
Model performance measures for the indicated outcomes using a random forest algorithm.</p
Performance metrics of the final prediction model on the test set using the random forest method.</p
<p>Observed versus predicted compressive strength produced by the SVM model (Training dataset).</p
<p>Diagnostic performance of a decision tree model with both training and validation datasets.</p
Response tree for the multivariable regression model for history of PrEP use.</p
Model predictions of response times by word gender and IAT pair in experiment 3.</p
Results of optimized parameter of the HKELM in the stage of ensemble learning.</p
Comparison of the performance of optimal experimental designs in supporting parameter inference for ...
The use of prediction error to optimize the number of splitting rules in a tree model does not contr...
<p>Prediction results of the original feature set and the optimal feature set.</p
Performance of machine learning models on test set using the ROSE-adjusted balanced training set.</p
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