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	0.997	k=28	Clustering
clusterdp	1.0	k=19 dc=0.7	Clustering
AGNES	1.0	method=single metric=euclidean k=6	Clustering
c-Means	1.0	k=11 m=1.5	Clustering
k-Medoids (PAM)	1.0	k=8	Clustering
DIANA	1.0	metric=euclidean k=12	Clustering
DBSCAN	1.0	eps=0.23333333333333334 MinPts=1	Clustering
Hierarchical Clustering	1.0	method=single k=4	Clustering
fanny	1.0	k=12 membexp=1.1	Clustering
clusterONE	1.0	s=1 d=0.43333333333333335	Clustering
Affinity Propagation	1.0	dampfact=0.9175 preference=5.25 maxits=2000 convits=200	Clustering
Markov Clustering	1.0	I=8.44984984984985	Clustering
Transitivity Clustering	1.0	T=0.11211211211211211	Clustering