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=420	Clustering
clusterdp	0.876	k=2 dc=0.9818135336715597	Clustering
AGNES	0.0	method=weighted metric=euclidean k=420	Clustering
c-Means	0.0	k=42 m=5.0	Clustering
k-Medoids (PAM)	0.0	k=414	Clustering
DIANA	0.0	metric=euclidean k=418	Clustering
DBSCAN	1.0	eps=0.9575649119003058 MinPts=224	Clustering
Hierarchical Clustering	0.0	method=complete k=418	Clustering
fanny	0.0	k=38 membexp=1.1	Clustering
clusterONE	1.0	s=420 d=0.8666666666666667	Clustering
Affinity Propagation	0.0	dampfact=0.9175 preference=1.0000000000000002 maxits=3500 convits=500	Clustering
Markov Clustering	1.0	I=8.405305305305305	Clustering
Transitivity Clustering	0.0	T=1.0000000000000002	Clustering
MCODE	0.266	v=0.8 cutoff=0.9962111528482418 haircut=T fluff=T	Clustering