Adverse event detection by integrating twitter data and VAERS

Table 2 Model performance between no formal report and 2500 formal report based on five metrics (the highest value for each metric is highlighted in bold type): multi-instance learning methods outperformed baselines

Method	Formal	ACC	PR	RE	FS	AUC
	#Report
SVM(linear)	0	0.7793	0.7309	0.6100	0.6644	0.7916
	2500	0.7296	0.6241	0.6370	0.6294	0.7234
SVM(poly)	0	0.6412	0.7231	0.3611	0.3069	0.5697
	2500	0.5478	0.5311	0.5497	0.4443	0.6416
SVM(rbf)	0	0.6507	0.6948	0.0572	0.1035	0.8069
	2500	0.5897	0.4652	0.9344	0.6210	0.7754
LR	0	0.7665	0.6765	0.6641	0.6700	0.7524
	2500	0.7322	0.6209	0.6576	0.6384	0.7303
NN	0	0.7924	0.7408	0.6273	0.6790	0.8196
	2500	0.7411	0.6414	0.6396	0.6394	0.7366
miFV	0	0.7818	0.7269	0.6352	0.6775	0.8348
	2500	0.7856	0.7331	0.6403	0.6833	0.8361
miVLAD	0	0.7691	0.7261	0.5832	0.6461	0.8390
	2500	0.7863	0.7055	0.6999	0.7018	0.8201
MILR	0	0.8034	0.7858	0.6231	0.6947	0.8676
	2500	0.8054	0.7871	0.6291	0.6984	0.8902

ISSN: 2041-1480