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=20 dc=0.4666666666666667	Clustering
AGNES	0.0	method=flexible metric=euclidean k=3	Clustering
c-Means	0.0	k=18 m=1.5	Clustering
k-Medoids (PAM)	0.0	k=33	Clustering
DIANA	0.0	metric=euclidean k=10	Clustering
DBSCAN	0.0	eps=6.3 MinPts=10	Clustering
Hierarchical Clustering	0.0	method=single k=4	Clustering
fanny	0.0	k=12 membexp=1.1	Clustering
clusterONE	0.0	s=2 d=0.36666666666666664	Clustering
Affinity Propagation	0.0	dampfact=0.7725 preference=1.75 maxits=5000 convits=200	Clustering
Markov Clustering	0.0	I=8.85075075075075	Clustering
Transitivity Clustering	0.0	T=4.848848848848849	Clustering