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	0.003	k=28	Clustering
clusterdp	0.0	k=16 dc=0.9333333333333333	Clustering
AGNES	0.0	method=complete metric=euclidean k=17	Clustering
c-Means	0.0	k=23 m=3.5	Clustering
k-Medoids (PAM)	0.0	k=5	Clustering
DIANA	0.0	metric=euclidean k=22	Clustering
DBSCAN	0.0	eps=4.433333333333334 MinPts=34	Clustering
Hierarchical Clustering	0.0	method=single k=4	Clustering
fanny	0.0	k=2 membexp=2.0	Clustering
clusterONE	0.0	s=1 d=0.7666666666666667	Clustering
Affinity Propagation	0.0	dampfact=0.845 preference=7.0 maxits=5000 convits=425	Clustering
Markov Clustering	0.0	I=8.672572572572573	Clustering
Transitivity Clustering	0.0	T=6.50950950950951	Clustering