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	0.69	k=4	Clustering
clusterdp	0.971	k=23 dc=3.033333333333333	Clustering
AGNES	1.0	method=average metric=euclidean k=2	Clustering
c-Means	1.0	k=2 m=5.0	Clustering
k-Medoids (PAM)	0.941	k=3	Clustering
DIANA	0.718	metric=euclidean k=9	Clustering
DBSCAN	0.668	eps=0.23333333333333334 MinPts=7	Clustering
Hierarchical Clustering	1.0	method=average k=2	Clustering
fanny	1.0	k=2 membexp=2.0	Clustering
clusterONE	0.848	s=6 d=0.23333333333333334	Clustering
Affinity Propagation	0.715	dampfact=0.99 preference=1.75 maxits=2000 convits=275	Clustering
Markov Clustering	1.0	I=1.5810810810810811	Clustering
Transitivity Clustering	1.0	T=0.08408408408408409	Clustering