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=278	Clustering
clusterdp	0.014	k=18 dc=0.8163114614680335	Clustering
AGNES	0.0	method=single metric=euclidean k=186	Clustering
c-Means	0.0	k=96 m=5.0	Clustering
k-Medoids (PAM)	0.0	k=38	Clustering
DIANA	0.0	metric=euclidean k=239	Clustering
DBSCAN	0.0	eps=0.7346721110093815 MinPts=273	Clustering
Hierarchical Clustering	0.0	method=average k=154	Clustering
fanny	0.0	k=57 membexp=5.0	Clustering
clusterONE	1.0	s=234 d=0.5333333333333333	Clustering
Affinity Propagation	0.0	dampfact=0.845 preference=0.5407786536700833 maxits=5000 convits=500	Clustering
Markov Clustering	1.0	I=9.93763763763764	Clustering
Transitivity Clustering	0.0	T=0.740126992534021	Clustering