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=293	Clustering
clusterdp	0.014	k=22 dc=0.8163114614680335	Clustering
AGNES	0.0	method=ward metric=euclidean k=253	Clustering
c-Means	0.0	k=69 m=5.0	Clustering
k-Medoids (PAM)	0.0	k=63	Clustering
DIANA	0.0	metric=euclidean k=37	Clustering
DBSCAN	0.0	eps=0.3877048715601111 MinPts=20	Clustering
Hierarchical Clustering	0.0	method=complete k=275	Clustering
fanny	0.0	k=293 membexp=2.0	Clustering
clusterONE	1.0	s=137 d=0.7666666666666667	Clustering
Affinity Propagation	0.0	dampfact=0.7725 preference=1.0 maxits=5000 convits=275	Clustering
Markov Clustering	1.0	I=8.173673673673674	Clustering
Transitivity Clustering	0.0	T=0.7033525103454392	Clustering