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	0.064	k=11	Clustering
clusterdp	0.0	k=24 dc=3.033333333333333	Clustering
AGNES	0.0	method=complete metric=euclidean k=2	Clustering
c-Means	0.0	k=26 m=1.01	Clustering
k-Medoids (PAM)	0.0	k=9	Clustering
DIANA	0.0	metric=euclidean k=7	Clustering
DBSCAN	0.0	eps=6.066666666666666 MinPts=2	Clustering
Hierarchical Clustering	0.0	method=average k=7	Clustering
fanny	0.0	k=2 membexp=2.0	Clustering
clusterONE	0.0	s=1 d=0.13333333333333333	Clustering
Affinity Propagation	0.0	dampfact=0.7725 preference=0.0 maxits=2000 convits=200	Clustering
Markov Clustering	0.0	I=9.305105105105104	Clustering
Transitivity Clustering	0.0	T=2.704704704704705	Clustering