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=2 dc=3.7333333333333334	Clustering
AGNES	0.0	method=ward metric=euclidean k=3	Clustering
c-Means	0.0	k=2 m=2.25	Clustering
k-Medoids (PAM)	0.0	k=27	Clustering
DIANA	0.0	metric=euclidean k=8	Clustering
DBSCAN	0.0	eps=5.833333333333333 MinPts=9	Clustering
Hierarchical Clustering	0.0	method=average k=19	Clustering
fanny	0.0	k=2 membexp=2.0	Clustering
clusterONE	0.0	s=3 d=0.9666666666666667	Clustering
Affinity Propagation	0.0	dampfact=0.99 preference=0.0 maxits=4250 convits=500	Clustering
Markov Clustering	0.0	I=6.730430430430431	Clustering
Transitivity Clustering	0.0	T=6.005005005005005	Clustering