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=22 dc=0.9387704871560112	Clustering
AGNES	1.0	method=complete metric=euclidean k=36	Clustering
c-Means	1.0	k=278 m=2.25	Clustering
k-Medoids (PAM)	1.0	k=279	Clustering
DIANA	1.0	metric=euclidean k=173	Clustering
DBSCAN	1.0	eps=0.6734425981653925 MinPts=273	Clustering
Hierarchical Clustering	1.0	method=single k=267	Clustering
fanny	1.0	k=111 membexp=5.0	Clustering
clusterONE	0.0	s=69 d=0.7333333333333333	Clustering
Affinity Propagation	1.0	dampfact=0.7725 preference=1.0 maxits=4250 convits=275	Clustering
Markov Clustering	0.0	I=3.30940940940941	Clustering
Transitivity Clustering	1.0	T=0.815514681020614	Clustering