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=506	Clustering
clusterdp	0.066	k=2 dc=197.34560741364413	Clustering
AGNES	0.0	method=average metric=euclidean k=210	Clustering
c-Means	0.0	k=481 m=1.01	Clustering
k-Medoids (PAM)	0.0	k=329	Clustering
DIANA	0.0	metric=euclidean k=242	Clustering
DBSCAN	0.0	eps=127.69421656176972 MinPts=439	Clustering
Hierarchical Clustering	0.0	method=single k=459	Clustering
fanny	0.0	k=172 membexp=5.0	Clustering
clusterONE	0.843	s=1 d=0.1	Clustering
Affinity Propagation	0.0	dampfact=0.99 preference=261.192715694529 maxits=3500 convits=425	Clustering
Markov Clustering	0.036	I=10.0	Clustering
Transitivity Clustering	0.0	T=314.44221495691045	Clustering