A Generative Clustering Ensemble Model and Its Application in IoT Data Analysis

Table 2

CAR metrics of different approaches on IoT datasets.

Datasets	Approaches
	-means	SV	SWV	EM	CoCE	WCT	HFEC	CSPA	U-SPEC	DEC	IDEC	VaDE	GCE
KDD’99	0.6784	0.7286	0.7585	0.8083	0.7864	0.8138	0.7966	0.8291	0.8336	0.8314	0.8303	0.8624	0.9062
NSL-KDD	0.7228	0.7550	0.7863	0.8465	0.8127	0.8359	0.8260	0.8332	0.8869	0.8103	0.8522	0.8539	0.9377
AWID	0.7680	0.8032	0.8266	0.8477	0.8543	0.8307	0.8644	0.8279	0.9093	0.7968	0.8377	0.8541	0.9362
UCI-IoT	0.6593	0.7362	0.7633	0.8005	0.7634	0.7441	0.7864	0.7533	0.8351	0.7608	0.8022	0.7879	0.9073
Synthetic dataset	0.7253	0.7498	0.7758	0.7531	0.8716	0.8242	0.7826	0.8331	0.8864	0.8174	0.8206	0.8376	0.9542