Fast Density Clustering Algorithm for Numerical Data and Categorical Data

Table 6

Clustering quality evaluation on all data sets.

Data sets	Algorithms	AC	Purity
Iris	-prototypes	0.819	0.842
	SBAC	0.426	0.46
	KL-FCM-GM	0.335	0.382
	IWKM	0.822	0.84
	DBSCAN	0.695	0.72
	BIRCH	0.86	0.89
	SpectralCAT	0.96	0.98
	TGCA	1.00	1.00
	FPC-MDACC	0.96	0.964
	FDCA	0.98	0.976
KDD CUP-99	-prototypes	0.84	0.862
	KL-FCM-GM	0.673	0.724
	IWKM	0.882	0.893
	DBSCAN	0.655	0.71
	BIRCH	0.72	0.763
	-modes	0.84	0.863
	Fuzzy -modes	0.87	0.887
	OCIL	0.916	0.928
	FPC-MDACC	0.938	0.945
	FDCA	0.95	0.961
Zoo	-prototypes	0.806	0.83
	KL-FCM-GM	0.426	0.485
	IWKM	0.864	0.843
	DBSCAN	0.629	0.694
	BIRCH	0.908	0.876
	-modes	0.42	0.53
	Fuzzy -modes	0.732	0.764
	OCIL	0.881	0.91
	FPC-MDACC	0.892	0.849
	FDCA	0.93	0.921
Heart	-prototypes	0.577	0.644
	SBAC	0.752	0778
	KL-FCM-GM	0.758	0.802
	EKP	0.545	0.589
	WFK-prototypes	0.835	0.826
	SpectralCAT	0.82	0.824
	OCIL	0.827	0.831
	FPC-MDACC	0.848	0.833
	FDCA	0.912	0.903
Breast cancer	-prototypes	0.84	0.862
	KL-FCM-GM	0.673	0.724
	IWKM	0.882	0.893
	DBSCAN	0.655	0.71
	BIRCH	0.72	0.763
	-modes	0.84	0.863
	Fuzzy -modes	0.87	0.887
	OCIL	0.916	0.928
	FPC-MDACC	0.938	0.945
	FDCA	0.97	0.97
Soybean	-prototypes	0.856	0.877
	KL-FCM-GM	0.617	0.642
	IWKM	0.903	0.895
	DBSCAN	0.908	0.922
	BIRCH	0.915	0.9
	-modes	0.957	0.985
	Fuzzy -modes	0.898	0.902
	OCIL	0.894	0.895
	FPC-MDACC	0.957	0.985
	FDCA	0.978	0.988
Acute	-prototypes	0.610	0.72
	SBAC	0.508	0556
	KL-FCM-GM	0.682	0.749
	EKP	0.508	0.586
	WFK-prototypes	0.710	0.765
	SpectralCAT	0.867	0.824
	OCIL	0.763	0.786
	FPC-MDACC	0.917	0.918
	FDCA	0.92	0.933
Credit	-prototypes	0.562	0.624
	SBAC	0.555	0.627
	KL-FCM-GM	0.574	0.632
	EKP	0.682	0.749
	IWKM	0.779	0.806
	WFK-prototypes	0.838	0.826
	SpectralCAT	0.77	0.794
	OCIL	0.713	0761
	FPC-MDACC	0.796	0.833
	FDCA	0.90	0.912