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=190	Clustering
clusterdp	0.33	k=22 dc=1.0000000000000002	Clustering
AGNES	1.0	method=flexible metric=euclidean k=162	Clustering
c-Means	1.0	k=26 m=1.5	Clustering
k-Medoids (PAM)	1.0	k=184	Clustering
DIANA	1.0	metric=euclidean k=186	Clustering
DBSCAN	0.0	eps=0.9237239211945912 MinPts=51	Clustering
Hierarchical Clustering	1.0	method=complete k=168	Clustering
fanny	1.0	k=13 membexp=5.0	Clustering
clusterONE	0.0	s=114 d=0.9666666666666667	Clustering
Affinity Propagation	1.0	dampfact=0.99 preference=1.0000000000000002 maxits=2750 convits=275	Clustering
Markov Clustering	0.0	I=9.42982982982983	Clustering
Transitivity Clustering	1.0	T=0.999758887059253	Clustering
MCODE	0.789	v=0.9 cutoff=0.994981836920697 haircut=T fluff=T	Clustering