K-Modes Clustering Algorithm Based on Weighted Overlap Distance and Its Application in Intrusion Detection

Table 2

Initialization results of different algorithms.

Datasets	Initializing methods
	Clustering	Random	Cao	Wu	Khan	Ini_Weight
Soybean	AC	0.8356	0.8812	0.8812	0.8911	0.9406
	PR	0.8186	0.8702	0.8702	0.7224	0.7676
	RE	0.6123	0.6714	0.6714	0.7716	0.8143
Zoo	AC	0.8356	0.8812	0.8812	0.8911	0.9406
	PR	0.8186	0.8702	0.8702	0.7224	0.7676
	RE	0.6123	0.6714	0.6714	0.7716	0.8143
	AC	0.8461	0.9113	0.9113	0.9127	0.9385
Breast	PR	0.8700	0.9292	0.9292	0.9318	0.9479
	RE	0.7833	0.8773	0.8773	0.8783	0.9167
	AC	0.7318	0.8754	0.8754	0.8815	0.8858
Mushroom	PR	0.7520	0.9019	0.9019	0.8975	0.9080
	RE	0.7278	0.8709	0.8709	0.8780	0.8817