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=511	Clustering
clusterdp	0.911	k=25 dc=0.9402323348407163	Clustering
AGNES	0.0	method=flexible metric=euclidean k=504	Clustering
c-Means	0.0	k=248 m=1.01	Clustering
k-Medoids (PAM)	0.0	k=506	Clustering
DIANA	0.0	metric=euclidean k=509	Clustering
DBSCAN	1.0	eps=0.9914617621201025 MinPts=494	Clustering
Hierarchical Clustering	0.0	method=single k=511	Clustering
fanny	0.0	k=507 membexp=1.1	Clustering
clusterONE	1.0	s=273 d=0.5333333333333333	Clustering
Affinity Propagation	0.0	dampfact=0.99 preference=1.0000000000000002 maxits=2000 convits=500	Clustering
Markov Clustering	1.0	I=8.351851851851851	Clustering
Transitivity Clustering	0.0	T=0.9997435964600633	Clustering
MCODE	0.284	v=0.0 cutoff=0.9946636013250642 haircut=T fluff=T	Clustering