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	1.0	k=507	Clustering
clusterdp	0.934	k=2 dc=197.34560741364413	Clustering
AGNES	1.0	method=weighted metric=euclidean k=93	Clustering
c-Means	1.0	k=440 m=3.5	Clustering
k-Medoids (PAM)	1.0	k=260	Clustering
DIANA	1.0	metric=euclidean k=267	Clustering
DBSCAN	1.0	eps=69.6513908518744 MinPts=439	Clustering
Hierarchical Clustering	1.0	method=complete k=482	Clustering
fanny	1.0	k=33 membexp=2.0	Clustering
clusterONE	0.157	s=1 d=0.06666666666666667	Clustering
Affinity Propagation	1.0	dampfact=0.845 preference=0.0 maxits=5000 convits=500	Clustering
Markov Clustering	0.964	I=9.946546546546546	Clustering
Transitivity Clustering	1.0	T=112.59959582159875	Clustering