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=104	Clustering
clusterdp	0.548	k=24 dc=0.967426237838838	Clustering
AGNES	0.0	method=weighted metric=euclidean k=105	Clustering
c-Means	0.0	k=68 m=1.5	Clustering
k-Medoids (PAM)	0.0	k=101	Clustering
DIANA	0.0	metric=euclidean k=104	Clustering
DBSCAN	1.0	eps=0.9650995405416121 MinPts=80	Clustering
Hierarchical Clustering	0.0	method=complete k=101	Clustering
fanny	0.0	k=26 membexp=1.1	Clustering
clusterONE	1.0	s=56 d=0.6333333333333333	Clustering
Affinity Propagation	0.0	dampfact=0.845 preference=1.0000000000000002 maxits=2000 convits=275	Clustering
Markov Clustering	1.0	I=1.108908908908909	Clustering
Transitivity Clustering	0.0	T=0.9996506460514678	Clustering