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	0.062	k=34	Clustering
clusterdp	0.391	k=13 dc=301.82269369145575	Clustering
AGNES	0.0	method=average metric=euclidean k=334	Clustering
c-Means	0.0	k=450 m=1.5	Clustering
k-Medoids (PAM)	0.0	k=156	Clustering
DIANA	0.0	metric=euclidean k=477	Clustering
DBSCAN	0.0	eps=313.4312588334348 MinPts=405	Clustering
Hierarchical Clustering	0.0	method=complete k=126	Clustering
fanny	0.076	k=157 membexp=5.0	Clustering
clusterONE	0.831	s=1 d=0.5666666666666667	Clustering
Affinity Propagation	0.0	dampfact=0.9175 preference=348.256954259372 maxits=5000 convits=350	Clustering
Markov Clustering	0.388	I=9.964364364364364	Clustering
Transitivity Clustering	0.0	T=72.85856200221096	Clustering