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=3
samples=20
Clustering
Self Organizing Maps 0.0 x=225
y=216
Clustering
Spectral Clustering 0.046 k=25 Clustering
clusterdp 0.0 k=22
dc=0.9925531892277383
Clustering
HDBSCAN 0.0 minPts=1
k=131
Clustering
AGNES 0.0 method=single
metric=euclidean
k=18
Clustering
c-Means 0.0 k=137
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=224 Clustering
DIANA 0.0 metric=euclidean
k=48
Clustering
DBSCAN 0.0 eps=0.36567749076811407
MinPts=1
Clustering
Hierarchical Clustering 0.0 method=complete
k=27
Clustering
fanny 0.0 k=62
membexp=1.1
Clustering
k-Means 0.0 k=88
nstart=10
Clustering
DensityCut 0.0 alpha=0.078125
K=12
Clustering
clusterONE 0.739 s=75
d=1.0
Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=0.7835946230745302
maxits=3500
convits=200
Clustering
Markov Clustering 0.739 I=1.206906906906907 Clustering
Transitivity Clustering 0.0 T=1.18127477712737 Clustering
MCODE 0.0 v=0.1
cutoff=1.1753919346117954
haircut=T
fluff=F
Clustering