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=507	Clustering
clusterdp	0.066	k=22 dc=174.128477129686	Clustering
AGNES	0.0	method=average metric=euclidean k=469	Clustering
c-Means	0.0	k=119 m=5.0	Clustering
k-Medoids (PAM)	0.0	k=416	Clustering
DIANA	0.0	metric=euclidean k=234	Clustering
DBSCAN	0.0	eps=23.21713028395813 MinPts=439	Clustering
Hierarchical Clustering	0.0	method=average k=146	Clustering
fanny	0.0	k=190 membexp=1.1	Clustering
clusterONE	0.843	s=1 d=0.9	Clustering
Affinity Propagation	0.0	dampfact=0.9175 preference=348.256954259372 maxits=5000 convits=350	Clustering
Markov Clustering	0.036	I=9.93763763763764	Clustering
Transitivity Clustering	0.0	T=15.33864463204441	Clustering