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=1046	Clustering
clusterdp	0.0	k=944 dc=16.011699733333334	Clustering
AGNES	0.0	method=single metric=euclidean k=537	Clustering
c-Means	0.0	k=128 m=5.0	Clustering
k-Medoids (PAM)	0.0	k=817	Clustering
DIANA	0.0	metric=euclidean k=605	Clustering
DBSCAN	0.0	eps=30.5677904 MinPts=803	Clustering
Hierarchical Clustering	0.0	method=complete k=821	Clustering
fanny	0.0	k=395 membexp=1.1	Clustering
clusterONE	1.0	s=838 d=0.6666666666666666	Clustering
Affinity Propagation	0.0	dampfact=0.99 preference=43.668272 maxits=2750 convits=425	Clustering
Markov Clustering	0.001	I=9.928728728728728	Clustering
Transitivity Clustering	0.0	T=9.66034846046046	Clustering
MCODE	0.024	v=0.4 cutoff=3.639022666666667 haircut=T fluff=T	Clustering