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=56
samples=20
Clustering
Self Organizing Maps 0.0 x=250
y=233
Clustering
Spectral Clustering 0.046 k=25 Clustering
clusterdp 0.0 k=17
dc=0.36567749076811407
Clustering
HDBSCAN 0.0 minPts=1
k=131
Clustering
AGNES 0.0 method=single
metric=euclidean
k=228
Clustering
c-Means 0.0 k=47
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=20 Clustering
DIANA 0.0 metric=euclidean
k=27
Clustering
DBSCAN 0.0 eps=0.36567749076811407
MinPts=1
Clustering
Hierarchical Clustering 0.0 method=average
k=244
Clustering
fanny 0.0 k=121
membexp=2.0
Clustering
k-Means 0.0 k=226
nstart=10
Clustering
DensityCut 0.0 alpha=0.23809523809523808
K=12
Clustering
clusterONE 0.739 s=59
d=0.06666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=0.0
maxits=4250
convits=350
Clustering
Markov Clustering 0.739 I=3.478678678678679 Clustering
Transitivity Clustering 0.0 T=1.408744687729586 Clustering
MCODE 0.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=T
Clustering