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	1.0	k=104	Clustering
clusterdp	0.452	k=21 dc=0.9720796324332898	Clustering
AGNES	1.0	method=ward metric=euclidean k=102	Clustering
c-Means	1.0	k=94 m=1.5	Clustering
k-Medoids (PAM)	1.0	k=101	Clustering
DIANA	1.0	metric=euclidean k=105	Clustering
DBSCAN	0.0	eps=0.946485962163805 MinPts=25	Clustering
Hierarchical Clustering	1.0	method=single k=105	Clustering
fanny	1.0	k=30 membexp=2.0	Clustering
clusterONE	0.0	s=66 d=0.9666666666666667	Clustering
Affinity Propagation	1.0	dampfact=0.9175 preference=1.0000000000000002 maxits=5000 convits=425	Clustering
Markov Clustering	0.0	I=8.61911911911912	Clustering
Transitivity Clustering	1.0	T=0.9996506460514678	Clustering