Semantic categorization of Chinese eligibility criteria in clinical trials using machine learning methods

Table 4 the overall classification performance comparison of 9 classifiers averaged in macro and micro level

Models	Macro-average			Micro-average
Models	Precision	Recall	F1-score	Precision	Recall	F1-score
Machine learning algorithms
NB	0.5398	0.7403	0.5965	0.6312	0.6312	0.6312
kNN	0.7531	0.6693	0.6948	0.7632	0.7632	0.7632
LR	0.8017	0.7574	0.7732	0.8173	0.8173	0.8173
SVM	0.8196	0.7712	0.7899	0.8293	0.8293	0.8293
Deep learning algorithms
CNN	0.8004	0.6951	0.7258	0.8142	0.8142	0.8142
RNN	0.7837	0.6925	0.7170	0.8138	0.8138	0.8138
FastText	0.7645	0.7188	0.7341	0.8182	0.8182	0.8182
Pre-trained language models
BERT	0.7994	0.8023	0.7958	0.8447	0.8447	0.8447
ERNIE	0.7964	0.8074	0.7980	0.8484	0.8484	0.8484

ISSN: 1472-6947