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	1.0	k=291	Clustering
clusterdp	0.986	k=2 dc=0.8775409743120223	Clustering
AGNES	1.0	method=weighted metric=euclidean k=179	Clustering
c-Means	1.0	k=278 m=5.0	Clustering
k-Medoids (PAM)	1.0	k=278	Clustering
DIANA	1.0	metric=euclidean k=160	Clustering
DBSCAN	1.0	eps=0.5713934100920778 MinPts=283	Clustering
Hierarchical Clustering	1.0	method=complete k=229	Clustering
fanny	1.0	k=115 membexp=5.0	Clustering
clusterONE	0.0	s=263 d=0.9333333333333333	Clustering
Affinity Propagation	1.0	dampfact=0.845 preference=0.8469262178900278 maxits=2750 convits=350	Clustering
Markov Clustering	0.0	I=4.173573573573573	Clustering
Transitivity Clustering	1.0	T=0.815514681020614	Clustering