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=278	Clustering
clusterdp	0.986	k=24 dc=0.6326229229360666	Clustering
AGNES	1.0	method=weighted metric=euclidean k=63	Clustering
c-Means	1.0	k=219 m=1.5	Clustering
k-Medoids (PAM)	1.0	k=43	Clustering
DIANA	1.0	metric=euclidean k=169	Clustering
DBSCAN	1.0	eps=0.7550819486240444 MinPts=215	Clustering
Hierarchical Clustering	1.0	method=single k=260	Clustering
fanny	1.0	k=64 membexp=2.0	Clustering
clusterONE	0.0	s=69 d=0.36666666666666664	Clustering
Affinity Propagation	1.0	dampfact=0.9175 preference=1.0 maxits=2750 convits=425	Clustering
Markov Clustering	0.0	I=4.316116116116116	Clustering
Transitivity Clustering	1.0	T=0.7959016238533703	Clustering