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=420	Clustering
clusterdp	0.124	k=3 dc=0.9242230569648314	Clustering
AGNES	1.0	method=ward metric=euclidean k=420	Clustering
c-Means	1.0	k=310 m=2.25	Clustering
k-Medoids (PAM)	1.0	k=419	Clustering
DIANA	1.0	metric=euclidean k=419	Clustering
DBSCAN	0.0	eps=0.930285212407645 MinPts=238	Clustering
Hierarchical Clustering	1.0	method=complete k=417	Clustering
fanny	1.0	k=78 membexp=1.1	Clustering
clusterONE	0.0	s=294 d=0.06666666666666667	Clustering
Affinity Propagation	1.0	dampfact=0.9175 preference=1.0000000000000002 maxits=4250 convits=200	Clustering
Markov Clustering	0.0	I=9.928728728728728	Clustering
Transitivity Clustering	1.0	T=1.0000000000000002	Clustering
MCODE	0.734	v=0.8 cutoff=0.9962111528482418 haircut=T fluff=T	Clustering