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=189	Clustering
clusterdp	0.67	k=4 dc=0.9478111039752466	Clustering
AGNES	0.0	method=complete metric=euclidean k=187	Clustering
c-Means	0.0	k=138 m=1.01	Clustering
k-Medoids (PAM)	0.0	k=167	Clustering
DIANA	0.0	metric=euclidean k=163	Clustering
DBSCAN	1.0	eps=0.9076657993408208 MinPts=101	Clustering
Hierarchical Clustering	0.0	method=complete k=175	Clustering
fanny	0.0	k=189 membexp=2.0	Clustering
clusterONE	1.0	s=1 d=0.06666666666666667	Clustering
Affinity Propagation	0.0	dampfact=0.9175 preference=1.0000000000000002 maxits=3500 convits=275	Clustering
Markov Clustering	1.0	I=9.412012012012012	Clustering
Transitivity Clustering	0.0	T=0.9992766611777584	Clustering
MCODE	0.211	v=0.9 cutoff=0.994981836920697 haircut=F fluff=T	Clustering