Confusion matrix showing the random forest model predictions for the independent testing dataset at 6, 12, and 24 months.</p
<p>To the left the results of the training sample that was used for tree building and on the right t...
The plot shows the predictive performances for the different methods when normalized data were class...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>Random Forest tree estimators displays higher OOB specificity than sensitivity. Area Under Curve ...
Features included in the model are: age group, sex, and laboratory blood test results of ten CBC par...
<p>The figure shows performance measures calculated for a multiclass random forest classifier that a...
A 14 × 14 confusion matrix: Prediction based on the LR-HeteNet method for the testing data .</p
<p>Confusion matrix and performance estimates of the multiclass prediction model.</p
<p>Confusion matrix for predicted monthly positive submissions with the prospective autoregressive i...
<p>A, C: ROC curves for the random forests models built on antibodies only (red line), exposure prox...
<p>(A) The confusion matrix of model probability, the estimated fraction of data simulated according...
A 14 × 14 confusion matrix: Prediction based on the MLR-HomoNet method for the testing data .</p
<p>Confusion matrix between predictions for individual classes based on hard90 and hard70 data for a...
<p>The confusion matrices of the unsupervised, semi-supervised, and supervised MTBNs for prediction ...
<p>Confusion matrix for classification by the statistical models versus the empirical models.</p
<p>To the left the results of the training sample that was used for tree building and on the right t...
The plot shows the predictive performances for the different methods when normalized data were class...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>Random Forest tree estimators displays higher OOB specificity than sensitivity. Area Under Curve ...
Features included in the model are: age group, sex, and laboratory blood test results of ten CBC par...
<p>The figure shows performance measures calculated for a multiclass random forest classifier that a...
A 14 × 14 confusion matrix: Prediction based on the LR-HeteNet method for the testing data .</p
<p>Confusion matrix and performance estimates of the multiclass prediction model.</p
<p>Confusion matrix for predicted monthly positive submissions with the prospective autoregressive i...
<p>A, C: ROC curves for the random forests models built on antibodies only (red line), exposure prox...
<p>(A) The confusion matrix of model probability, the estimated fraction of data simulated according...
A 14 × 14 confusion matrix: Prediction based on the MLR-HomoNet method for the testing data .</p
<p>Confusion matrix between predictions for individual classes based on hard90 and hard70 data for a...
<p>The confusion matrices of the unsupervised, semi-supervised, and supervised MTBNs for prediction ...
<p>Confusion matrix for classification by the statistical models versus the empirical models.</p
<p>To the left the results of the training sample that was used for tree building and on the right t...
The plot shows the predictive performances for the different methods when normalized data were class...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
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