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	0.37	k=2	Clustering
clusterdp	0.886	k=19 dc=1.1666666666666667	Clustering
AGNES	1.0	method=flexible metric=euclidean k=1	Clustering
c-Means	1.0	k=2 m=2.25	Clustering
k-Medoids (PAM)	0.795	k=7	Clustering
DIANA	0.601	metric=euclidean k=9	Clustering
DBSCAN	0.487	eps=0.0 MinPts=3	Clustering
Hierarchical Clustering	1.0	method=average k=2	Clustering
fanny	1.0	k=2 membexp=2.0	Clustering
clusterONE	0.601	s=6 d=0.0	Clustering
Affinity Propagation	0.374	dampfact=0.7725 preference=1.75 maxits=5000 convits=425	Clustering
Markov Clustering	1.0	I=1.50980980980981	Clustering
Transitivity Clustering	1.0	T=0.11211211211211211	Clustering