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	0.998	k=2	Clustering
clusterdp	0.994	k=2 dc=0.8932720265012789	Clustering
AGNES	1.0	method=ward metric=euclidean k=1	Clustering
c-Means	0.921	k=2 m=1.5	Clustering
k-Medoids (PAM)	0.794	k=2	Clustering
DIANA	1.0	metric=euclidean k=3	Clustering
DBSCAN	1.0	eps=0.9487705727206139 MinPts=188	Clustering
Hierarchical Clustering	0.994	method=average k=2	Clustering
fanny	1.0	k=24 membexp=2.0	Clustering
clusterONE	1.0	s=392 d=0.3333333333333333	Clustering
Affinity Propagation	0.395	dampfact=0.7725 preference=0.8719264318015347 maxits=4250 convits=350	Clustering
Markov Clustering	1.0	I=7.024424424424424	Clustering
Transitivity Clustering	1.0	T=0.9232071397889083	Clustering
MCODE	0.574	v=0.2 cutoff=0.9946636013250642 haircut=F fluff=F	Clustering