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	0.497	k=5	Clustering
clusterdp	0.999	k=2 dc=0.8367212990826963	Clustering
AGNES	1.0	method=complete metric=euclidean k=1	Clustering
c-Means	0.988	k=2 m=1.5	Clustering
k-Medoids (PAM)	0.97	k=2	Clustering
DIANA	1.0	metric=euclidean k=1	Clustering
DBSCAN	1.0	eps=0.4897540596334259 MinPts=20	Clustering
Hierarchical Clustering	1.0	method=single k=3	Clustering
fanny	1.0	k=4 membexp=2.0	Clustering
clusterONE	1.0	s=293 d=0.4	Clustering
Affinity Propagation	0.133	dampfact=0.7 preference=0.387704871560111 maxits=2000 convits=425	Clustering
Markov Clustering	1.0	I=1.1979979979979982	Clustering
Transitivity Clustering	1.0	T=0.4465440430618421	Clustering