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=293	Clustering
clusterdp	0.986	k=22 dc=0.7754917862387074	Clustering
AGNES	1.0	method=weighted metric=euclidean k=44	Clustering
c-Means	1.0	k=101 m=1.5	Clustering
k-Medoids (PAM)	1.0	k=94	Clustering
DIANA	1.0	metric=euclidean k=111	Clustering
DBSCAN	1.0	eps=0.7142622733947185 MinPts=244	Clustering
Hierarchical Clustering	1.0	method=single k=233	Clustering
fanny	1.0	k=34 membexp=2.0	Clustering
clusterONE	0.0	s=88 d=0.4	Clustering
Affinity Propagation	1.0	dampfact=0.9175 preference=0.6938524357800555 maxits=3500 convits=425	Clustering
Markov Clustering	0.0	I=3.3450450450450453	Clustering
Transitivity Clustering	1.0	T=0.8706764043034869	Clustering