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=103	Clustering
clusterdp	0.548	k=8 dc=1.0000000000000002	Clustering
AGNES	0.0	method=ward metric=euclidean k=102	Clustering
c-Means	0.0	k=41 m=2.25	Clustering
k-Medoids (PAM)	0.0	k=102	Clustering
DIANA	0.0	metric=euclidean k=105	Clustering
DBSCAN	1.0	eps=0.9488126594610308 MinPts=39	Clustering
Hierarchical Clustering	0.0	method=complete k=104	Clustering
fanny	0.0	k=47 membexp=1.1	Clustering
clusterONE	1.0	s=4 d=0.6	Clustering
Affinity Propagation	0.0	dampfact=0.7725 preference=1.0000000000000002 maxits=2750 convits=350	Clustering
Markov Clustering	1.0	I=4.717017017017017	Clustering
Transitivity Clustering	0.0	T=0.9998602584205872	Clustering