Table 3 Classification performance of the weak and ensemble classifiers.

From: A novel hybrid supervised and unsupervised hierarchical ensemble for COVID-19 cases and mortality prediction

Model

Accuracy

ROC-AUC

F1-score

GM

0.614

0.616

0.616

Decision tree

0.713

0.715

0.715

SVM linear

0.733

0.732

0.735

KNN + 10-folds cross-validation

0.816

0.797

0.814

XGBoost

0.797

0.797

0.806

RBF

0.675

0.719

0.716

Random forest

0.725

0.728

0.728

Naïve Bayes

0.721

Nfble0.728

0.724

Ml (c(4, 3, 3))

0.733

0.732

0.735

Ensemble 1

0.895

0.897

0.897

Ensemble 2

0.912

0.916

0.916

  1. Significant values are given in bold.
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