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=16 dc=1.0	Clustering
AGNES	0.0	method=ward metric=euclidean k=12	Clustering
c-Means	0.0	k=207 m=3.5	Clustering
k-Medoids (PAM)	0.0	k=66	Clustering
DIANA	0.0	metric=euclidean k=190	Clustering
DBSCAN	0.0	eps=0.5101638972480889 MinPts=1	Clustering
Hierarchical Clustering	0.0	method=single k=119	Clustering
fanny	0.0	k=88 membexp=1.1	Clustering
clusterONE	1.0	s=127 d=0.13333333333333333	Clustering
Affinity Propagation	0.0	dampfact=0.845 preference=0.6938524357800555 maxits=2000 convits=425	Clustering
Markov Clustering	1.0	I=6.605705705705706	Clustering
Transitivity Clustering	0.0	T=0.9969354598176182	Clustering