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=508	Clustering
clusterdp	0.911	k=24 dc=0.9231558590809209	Clustering
AGNES	0.0	method=complete metric=euclidean k=511	Clustering
c-Means	0.0	k=38 m=1.5	Clustering
k-Medoids (PAM)	0.0	k=506	Clustering
DIANA	0.0	metric=euclidean k=511	Clustering
DBSCAN	1.0	eps=0.9359632159007674 MinPts=341	Clustering
Hierarchical Clustering	0.0	method=complete k=511	Clustering
fanny	0.0	k=167 membexp=5.0	Clustering
clusterONE	1.0	s=273 d=0.5333333333333333	Clustering
Affinity Propagation	0.0	dampfact=0.99 preference=1.0000000000000002 maxits=5000 convits=275	Clustering
Markov Clustering	1.0	I=5.037737737737738	Clustering
Transitivity Clustering	0.0	T=0.9997435964600633	Clustering
MCODE	0.284	v=0.0 cutoff=0.9946636013250642 haircut=T fluff=F	Clustering