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	0.609	k=11 dc=0.9860398162166449	Clustering
AGNES	0.0	method=average metric=euclidean k=102	Clustering
c-Means	0.0	k=102 m=1.01	Clustering
k-Medoids (PAM)	0.0	k=102	Clustering
DIANA	0.0	metric=euclidean k=102	Clustering
DBSCAN	0.613	eps=0.9860398162166449 MinPts=28	Clustering
Hierarchical Clustering	0.0	method=single k=102	Clustering
fanny	0.523	k=48 membexp=1.1	Clustering
clusterONE	0.613	s=56 d=0.9666666666666667	Clustering
Affinity Propagation	0.578	dampfact=0.99 preference=0.9650995405416121 maxits=3500 convits=425	Clustering
Markov Clustering	0.613	I=6.062262262262263	Clustering
Transitivity Clustering	0.0	T=0.9997205168411744	Clustering