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=3 dc=1.4	Clustering
AGNES	0.0	method=flexible metric=euclidean k=19	Clustering
c-Means	0.0	k=2 m=1.01	Clustering
k-Medoids (PAM)	0.0	k=32	Clustering
DIANA	0.0	metric=euclidean k=16	Clustering
DBSCAN	0.0	eps=5.833333333333333 MinPts=9	Clustering
Hierarchical Clustering	0.0	method=average k=11	Clustering
fanny	0.0	k=12 membexp=1.1	Clustering
clusterONE	0.0	s=1 d=0.43333333333333335	Clustering
Affinity Propagation	0.0	dampfact=0.99 preference=7.0 maxits=2750 convits=275	Clustering
Markov Clustering	0.0	I=2.596696696696697	Clustering
Transitivity Clustering	0.0	T=0.9039039039039038	Clustering