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	0.0	k=291	Clustering
clusterdp	0.014	k=18 dc=0.8775409743120223	Clustering
AGNES	0.0	method=ward metric=euclidean k=71	Clustering
c-Means	0.0	k=281 m=1.5	Clustering
k-Medoids (PAM)	0.0	k=183	Clustering
DIANA	0.0	metric=euclidean k=53	Clustering
DBSCAN	0.0	eps=0.6734425981653925 MinPts=273	Clustering
Hierarchical Clustering	0.0	method=single k=277	Clustering
fanny	0.0	k=113 membexp=2.0	Clustering
clusterONE	1.0	s=195 d=0.26666666666666666	Clustering
Affinity Propagation	0.0	dampfact=0.99 preference=1.0 maxits=5000 convits=425	Clustering
Markov Clustering	1.0	I=5.83953953953954	Clustering
Transitivity Clustering	0.0	T=0.7793531068685084	Clustering