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=291	Clustering
clusterdp	0.986	k=20 dc=0.8979508119266852	Clustering
AGNES	1.0	method=flexible metric=euclidean k=25	Clustering
c-Means	1.0	k=275 m=2.25	Clustering
k-Medoids (PAM)	1.0	k=157	Clustering
DIANA	1.0	metric=euclidean k=153	Clustering
DBSCAN	1.0	eps=0.4897540596334259 MinPts=10	Clustering
Hierarchical Clustering	1.0	method=complete k=220	Clustering
fanny	1.0	k=64 membexp=2.0	Clustering
clusterONE	0.0	s=273 d=0.0	Clustering
Affinity Propagation	1.0	dampfact=0.99 preference=0.8469262178900278 maxits=2750 convits=275	Clustering
Markov Clustering	0.0	I=1.9285285285285287	Clustering
Transitivity Clustering	1.0	T=0.5501255012263478	Clustering