Clusteval logo ClustEval clustering evaluation framework

Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:
Program Best quality Parameter set Clustering
CLARA 0.0 metric=euclidean
k=52
samples=20
Clustering
Self Organizing Maps 0.0 x=2
y=34
Clustering
Spectral Clustering 0.0 k=17 Clustering
clusterdp 0.0 k=19
dc=1.5664824497498762
Clustering
HDBSCAN 0.0 minPts=60
k=214
Clustering
AGNES 0.0 method=single
metric=euclidean
k=180
Clustering
c-Means 0.0 k=37
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=25 Clustering
DIANA 0.0 metric=euclidean
k=45
Clustering
DBSCAN 0.0 eps=1.8275628580415222
MinPts=200
Clustering
Hierarchical Clustering 0.0 method=complete
k=240
Clustering
fanny 0.0 k=68
membexp=2.0
Clustering
k-Means 0.0 k=167
nstart=10
Clustering
DensityCut 0.0 alpha=0.9453125
K=3
Clustering
clusterONE 1.0 s=59
d=0.5666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=0.9790515310936726
maxits=2000
convits=275
Clustering
Markov Clustering 1.0 I=1.385085085085085 Clustering
Transitivity Clustering 0.0 T=3.0380978442346196 Clustering
MCODE 0.001 v=0.6
cutoff=3.589855614010133
haircut=F
fluff=F
Clustering