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=511	Clustering
clusterdp	0.089	k=25 dc=0.9445014537806652	Clustering
AGNES	1.0	method=weighted metric=euclidean k=511	Clustering
c-Means	1.0	k=187 m=1.5	Clustering
k-Medoids (PAM)	1.0	k=510	Clustering
DIANA	1.0	metric=euclidean k=511	Clustering
DBSCAN	0.0	eps=0.8847337886213812 MinPts=239	Clustering
Hierarchical Clustering	1.0	method=complete k=511	Clustering
fanny	1.0	k=103 membexp=2.0	Clustering
clusterONE	0.0	s=307 d=0.8666666666666667	Clustering
Affinity Propagation	1.0	dampfact=0.9175 preference=1.0000000000000002 maxits=2000 convits=200	Clustering
Markov Clustering	0.0	I=9.964364364364364	Clustering
Transitivity Clustering	1.0	T=0.9997435964600633	Clustering
MCODE	0.716	v=0.0 cutoff=0.9946636013250642 haircut=T fluff=F	Clustering