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=131
samples=20
Clustering
Self Organizing Maps 0.0 x=26
y=92
Clustering
Spectral Clustering 0.046 k=25 Clustering
clusterdp 0.0 k=23
dc=0.8880739061511342
Clustering
HDBSCAN 0.0 minPts=36
k=24
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=7
Clustering
c-Means 0.0 k=5
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=197 Clustering
DIANA 0.0 metric=euclidean
k=165
Clustering
DBSCAN 0.0 eps=0.36567749076811407
MinPts=1
Clustering
Hierarchical Clustering 0.0 method=average
k=167
Clustering
fanny 0.0 k=24
membexp=5.0
Clustering
k-Means 0.0 k=245
nstart=10
Clustering
DensityCut 0.0 alpha=0.043261054421768703
K=12
Clustering
clusterONE 0.739 s=233
d=0.5333333333333333
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=1.1753919346117954
maxits=2750
convits=200
Clustering
Markov Clustering 0.739 I=8.904204204204206 Clustering
Transitivity Clustering 0.0 T=1.549932908103375 Clustering
MCODE 0.0 v=0.1
cutoff=1.1753919346117954
haircut=T
fluff=F
Clustering