EURASIP Journal on Advances in Signal Processing

Table 2 The performance achieved by the schemes TGSm-St-GL, GSm-St-GL, TVGL-TS and TVGL-SV while learning time-varying graphs

From: Time-varying graph learning from smooth and stationary graph signals with hidden nodes

Datasets	Algorithm	Fscore	Precision	Recall	NMI
PM 2.5	TGSm-St-GL	0.5011	0.5597	0.4605	0.1249
	GSm-St-GL	0.3672	0.2268	0.9721	3.049e−5
	TVGL-TS	0.2268	0.5055	0.1628	0.0409
	TVGL-SV	0.2295	0.5257	0.1488	0.0430
COVID-19	TGSm-St-GL	0.2629	0.1775	0.7890	0.0603
	GSm-St-GL	0.2546	0.1496	0.8923	0.0410
	TVGL-TS	0.0938	0.1494	0.2967	0.0590
	TVGL-SV	0.1577	0.1494	0.5627	0.0290

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