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	0.583	k=4	Clustering
clusterdp	0.975	k=24 dc=0.9557927513527085	Clustering
AGNES	1.0	method=ward metric=euclidean k=2	Clustering
c-Means	0.854	k=2 m=1.5	Clustering
k-Medoids (PAM)	0.951	k=2	Clustering
DIANA	1.0	metric=euclidean k=1	Clustering
DBSCAN	1.0	eps=0.9976733027027743 MinPts=4	Clustering
Hierarchical Clustering	0.975	method=average k=3	Clustering
fanny	1.0	k=9 membexp=1.1	Clustering
clusterONE	1.0	s=66 d=0.5666666666666667	Clustering
Affinity Propagation	1.0	dampfact=0.845 preference=0.9476493108124179 maxits=5000 convits=425	Clustering
Markov Clustering	1.0	I=6.552252252252253	Clustering
Transitivity Clustering	1.0	T=0.9357887442597425	Clustering