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=103	Clustering
clusterdp	0.452	k=8 dc=0.9906932108110967	Clustering
AGNES	1.0	method=weighted metric=euclidean k=103	Clustering
c-Means	1.0	k=3 m=1.01	Clustering
k-Medoids (PAM)	1.0	k=103	Clustering
DIANA	1.0	metric=euclidean k=105	Clustering
DBSCAN	0.0	eps=0.9860398162166449 MinPts=32	Clustering
Hierarchical Clustering	1.0	method=single k=104	Clustering
fanny	1.0	k=24 membexp=5.0	Clustering
clusterONE	0.0	s=77 d=0.8	Clustering
Affinity Propagation	1.0	dampfact=0.845 preference=1.0000000000000002 maxits=5000 convits=500	Clustering
Markov Clustering	0.0	I=9.955455455455455	Clustering
Transitivity Clustering	1.0	T=0.9996506460514678	Clustering