A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System

Table 3

Results on the synthetic datasets.

Algorithm	Par	C1	Acc	NMI	Algorithm	Par	C1	Acc	NMI
Spiral					Compound
KST-DPC	16	3	1.00	1.00	KST-DPC	217	6	0.98	0.95
DPC-KNN	20	3	1.00	1.00	DPC-KNN	360	6	0.6466	0.7663
DBSCAN	1.2/3	3	1.00	1.00	DBSCAN	1.5/3	5	0.8596	0.9429
SC	3	3	1.00	1.00	SC	6	6	0.6015	0.7622
Jain					Aggregation
KST-DPC	4	2	1.00	1.00	KST-DPC	40	7	1.00	1.00
DPC-KNN	8	2	0.9035	0.5972	DPC-KNN	40	7	0.9987	0.9957
DBSCAN	2.62/4	2	1.00	1.00	DBSCAN	1.59/3	5	0.8274	0.8894
SC	2	2	1.00	1.00	SC	7	7	0.9937	0.9824
R15					D31
KST-DPC	20	15	1.00	0.99	KST-DPC	25	31	1.0000	1.0000
DPC-KNN	20	15	1.00	0.99	DPC-KNN	25	31	0.9700	0.9500
DBSCAN	0.4/5	13	0.78	0.9155	DBSCAN	0.46/3	27	0.6516	0.8444
SC	15	15	0.9967	0.9942	SC	31	31	0.9765	0.9670