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=104	Clustering
clusterdp	0.452	k=22 dc=0.9860398162166449	Clustering
AGNES	1.0	method=single metric=euclidean k=103	Clustering
c-Means	1.0	k=80 m=3.5	Clustering
k-Medoids (PAM)	1.0	k=101	Clustering
DIANA	1.0	metric=euclidean k=105	Clustering
DBSCAN	0.0	eps=0.9441592648665791 MinPts=94	Clustering
Hierarchical Clustering	1.0	method=complete k=104	Clustering
fanny	1.0	k=19 membexp=2.0	Clustering
clusterONE	0.0	s=80 d=0.1	Clustering
Affinity Propagation	1.0	dampfact=0.845 preference=1.0000000000000002 maxits=5000 convits=500	Clustering
Markov Clustering	0.0	I=1.4474474474474475	Clustering
Transitivity Clustering	1.0	T=0.9996506460514678	Clustering