ClustEval | Which parameter sets lead to the optimal clustering quality?

ClustEval clustering evaluation framework

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Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:

Program	Best quality	Parameter set	Clustering
Spectral Clustering	0.0	k=103	Clustering
clusterdp	0.548	k=25 dc=0.9301990810832238	Clustering
AGNES	0.0	method=ward metric=euclidean k=105	Clustering
c-Means	0.0	k=57 m=5.0	Clustering
k-Medoids (PAM)	0.0	k=101	Clustering
DIANA	0.0	metric=euclidean k=104	Clustering
DBSCAN	1.0	eps=0.9720796324332898 MinPts=25	Clustering
Hierarchical Clustering	0.0	method=complete k=105	Clustering
fanny	0.0	k=20 membexp=2.0	Clustering
clusterONE	1.0	s=28 d=0.7333333333333333	Clustering
Affinity Propagation	0.0	dampfact=0.845 preference=1.0000000000000002 maxits=3500 convits=350	Clustering
Markov Clustering	1.0	I=1.3227227227227227	Clustering
Transitivity Clustering	0.0	T=0.9996506460514678	Clustering