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=293	Clustering
clusterdp	0.986	k=22 dc=0.8367212990826963	Clustering
AGNES	1.0	method=weighted metric=euclidean k=179	Clustering
c-Means	1.0	k=278 m=1.01	Clustering
k-Medoids (PAM)	1.0	k=278	Clustering
DIANA	1.0	metric=euclidean k=154	Clustering
DBSCAN	1.0	eps=0.5509835724774148 MinPts=283	Clustering
Hierarchical Clustering	1.0	method=average k=229	Clustering
fanny	1.0	k=47 membexp=5.0	Clustering
clusterONE	0.0	s=244 d=0.6333333333333333	Clustering
Affinity Propagation	1.0	dampfact=0.7 preference=0.8469262178900278 maxits=2750 convits=350	Clustering
Markov Clustering	0.0	I=3.541041041041041	Clustering
Transitivity Clustering	1.0	T=0.9760965865774218	Clustering