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	0.064	k=11	Clustering
clusterdp	0.0	k=19 dc=0.7	Clustering
AGNES	0.0	method=average metric=euclidean k=32	Clustering
c-Means	0.0	k=9 m=1.5	Clustering
k-Medoids (PAM)	0.0	k=20	Clustering
DIANA	0.0	metric=euclidean k=13	Clustering
DBSCAN	0.0	eps=6.066666666666666 MinPts=2	Clustering
Hierarchical Clustering	0.0	method=average k=19	Clustering
fanny	0.0	k=2 membexp=2.0	Clustering
clusterONE	0.0	s=5 d=0.16666666666666666	Clustering
Affinity Propagation	0.0	dampfact=0.9175 preference=1.75 maxits=4250 convits=425	Clustering
Markov Clustering	0.0	I=9.973273273273273	Clustering
Transitivity Clustering	0.0	T=3.3563563563563563	Clustering