ClustEval | Which parameter sets lead to the optimal clustering quality?

ClustEval clustering evaluation framework

Navigation:

027

Hints:

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=22 dc=1.0	Clustering
AGNES	1.0	method=ward metric=euclidean k=19	Clustering
c-Means	1.0	k=263 m=2.25	Clustering
k-Medoids (PAM)	1.0	k=160	Clustering
DIANA	1.0	metric=euclidean k=246	Clustering
DBSCAN	1.0	eps=0.428524546789437 MinPts=10	Clustering
Hierarchical Clustering	1.0	method=complete k=293	Clustering
fanny	1.0	k=137 membexp=5.0	Clustering
clusterONE	0.0	s=117 d=0.8	Clustering
Affinity Propagation	1.0	dampfact=0.9175 preference=1.0 maxits=3500 convits=200	Clustering
Markov Clustering	0.0	I=2.56996996996997	Clustering
Transitivity Clustering	1.0	T=0.815514681020614	Clustering