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=278	Clustering
clusterdp	0.014	k=19 dc=0.7959016238533704	Clustering
AGNES	0.0	method=average metric=euclidean k=203	Clustering
c-Means	0.0	k=234 m=1.01	Clustering
k-Medoids (PAM)	0.0	k=283	Clustering
DIANA	0.0	metric=euclidean k=172	Clustering
DBSCAN	0.0	eps=0.6530327605507296 MinPts=1	Clustering
Hierarchical Clustering	0.0	method=average k=185	Clustering
fanny	0.0	k=51 membexp=5.0	Clustering
clusterONE	1.0	s=234 d=0.2	Clustering
Affinity Propagation	0.0	dampfact=0.99 preference=0.6938524357800555 maxits=5000 convits=200	Clustering
Markov Clustering	1.0	I=6.053353353353354	Clustering
Transitivity Clustering	0.0	T=0.6825136371052428	Clustering