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	1.0	k=103	Clustering
clusterdp	0.452	k=23 dc=0.9371791729749014	Clustering
AGNES	1.0	method=average metric=euclidean k=102	Clustering
c-Means	1.0	k=12 m=1.01	Clustering
k-Medoids (PAM)	1.0	k=101	Clustering
DIANA	1.0	metric=euclidean k=105	Clustering
DBSCAN	0.0	eps=0.9837131189194191 MinPts=87	Clustering
Hierarchical Clustering	1.0	method=complete k=101	Clustering
fanny	1.0	k=49 membexp=1.1	Clustering
clusterONE	0.0	s=80 d=1.0	Clustering
Affinity Propagation	1.0	dampfact=0.7725 preference=1.0000000000000002 maxits=2750 convits=425	Clustering
Markov Clustering	0.0	I=9.946546546546546	Clustering
Transitivity Clustering	1.0	T=0.9996506460514678	Clustering