Classifying publications from the clinical and translational science award program along the translational research spectrum: a machine learning approach

Table 5 AUC and performance ranges for each classifier with different machine learning algorithms

Classifier	Translational class
Classifier	T0	T1/T2	T3/T4
Naïve Bayes	0.91 (0.80–0.97)	0.78 (0.45–0.97)	0.87 (0.72–0.97)
Liblinear (linear support vector machine)	0.94 (0.93–0.96)	0.84 (0.76–0.98)	0.92 (0.90–0.94)
Random forest	0.94 (0.84–0.98)	0.84 (0.75–0.98)	0.87 (0.72–0.98)
Bayesian logistic regression	0.92 (0.82–0.99)	0.84 (0.53–0.99)	0.92 (0.82–0.99)

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