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	0.0	k=1046	Clustering
clusterdp	0.0	k=769 dc=34.9346176	Clustering
AGNES	0.0	method=average metric=euclidean k=780	Clustering
c-Means	0.0	k=1017 m=2.25	Clustering
k-Medoids (PAM)	0.0	k=990	Clustering
DIANA	0.0	metric=euclidean k=866	Clustering
DBSCAN	0.0	eps=17.4673088 MinPts=699	Clustering
Hierarchical Clustering	0.0	method=average k=736	Clustering
fanny	0.0	k=213 membexp=1.1	Clustering
clusterONE	1.0	s=524 d=0.7333333333333333	Clustering
Affinity Propagation	0.0	dampfact=0.9175 preference=43.668272 maxits=2000 convits=275	Clustering
Markov Clustering	0.001	I=9.928728728728728	Clustering
Transitivity Clustering	0.0	T=31.079220612612612	Clustering
MCODE	0.024	v=0.4 cutoff=3.639022666666667 haircut=F fluff=T	Clustering