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=291	Clustering
clusterdp	0.014	k=24 dc=0.8367212990826963	Clustering
AGNES	0.0	method=single metric=euclidean k=82	Clustering
c-Means	0.0	k=243 m=5.0	Clustering
k-Medoids (PAM)	0.0	k=110	Clustering
DIANA	0.0	metric=euclidean k=71	Clustering
DBSCAN	0.0	eps=0.3877048715601111 MinPts=20	Clustering
Hierarchical Clustering	0.0	method=average k=240	Clustering
fanny	0.0	k=96 membexp=1.1	Clustering
clusterONE	1.0	s=273 d=0.36666666666666664	Clustering
Affinity Propagation	0.0	dampfact=0.7725 preference=1.0 maxits=5000 convits=275	Clustering
Markov Clustering	1.0	I=5.1980980980980975	Clustering
Transitivity Clustering	0.0	T=0.8933540016531124	Clustering