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	0.691	k=2	Clustering
clusterdp	0.97	k=3 dc=3.966666666666667	Clustering
AGNES	1.0	method=complete metric=euclidean k=2	Clustering
c-Means	1.0	k=2 m=3.5	Clustering
k-Medoids (PAM)	0.94	k=3	Clustering
DIANA	0.834	metric=euclidean k=17	Clustering
DBSCAN	0.834	eps=4.433333333333334 MinPts=4	Clustering
Hierarchical Clustering	1.0	method=average k=2	Clustering
fanny	1.0	k=2 membexp=2.0	Clustering
clusterONE	0.847	s=6 d=0.0	Clustering
Affinity Propagation	0.612	dampfact=0.99 preference=0.0 maxits=5000 convits=500	Clustering
Markov Clustering	1.0	I=1.50980980980981	Clustering
Transitivity Clustering	1.0	T=0.11211211211211211	Clustering