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=278
samples=20
Clustering
Self Organizing Maps 0.0 x=300
y=230
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=21
dc=0.9765301383526837
Clustering
HDBSCAN 0.0 minPts=80
k=180
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=238
Clustering
c-Means 0.0 k=125
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=174 Clustering
DIANA 0.0 metric=euclidean
k=292
Clustering
DBSCAN 0.0 eps=7.812241106821469
MinPts=250
Clustering
Hierarchical Clustering 0.0 method=complete
k=105
Clustering
fanny 0.0 k=99
membexp=5.0
Clustering
k-Means 0.0 k=297
nstart=10
Clustering
DensityCut 0.005 alpha=0.06914682539682541
K=2
Clustering
clusterONE 0.667 s=170
d=0.36666666666666664
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=29.29590415058051
maxits=5000
convits=500
Clustering
Markov Clustering 0.471 I=9.893093093093094 Clustering
Transitivity Clustering 0.0 T=27.800317452202524 Clustering