The random forest model significantly outperformed all other models, including the logistic regression model that the entire paper focuses on, with an eventual AUC of 0.936 and an accuracy of 0.918.

Regression using step and logistic models yields thresholds of 185 cm (solid vertical blue line) and 194 cm (dashed blue line), respectively. The outlier from a does not substantially affect ...

The classification boundary is shown by the black line. Logistic Regression attains an accuracy of 0.969 and a F1-score of 0.628.

The support vector machine (SVM) is known for its good performance in two-class classification, but its extension to multiclass classification is still an ongoing research issue. In this article, we ...

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