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=67
samples=20
Clustering
Self Organizing Maps 0.0 x=12
y=135
Clustering
Spectral Clustering 0.0 k=52 Clustering
clusterdp 0.0 k=22
dc=24.24620382657871
Clustering
HDBSCAN 0.0 minPts=1
k=218
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=13
Clustering
c-Means 0.0 k=255
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=53 Clustering
DIANA 0.0 metric=euclidean
k=62
Clustering
DBSCAN 0.0 eps=16.164135884385807
MinPts=280
Clustering
Hierarchical Clustering 0.0 method=complete
k=224
Clustering
fanny 0.0 k=46
membexp=2.0
Clustering
k-Means 0.0 k=289
nstart=10
Clustering
DensityCut 0.0 alpha=0.13392857142857142
K=3
Clustering
clusterONE 0.669 s=1
d=1.0
Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=22.73081608741754
maxits=5000
convits=425
Clustering
Markov Clustering 0.669 I=4.601201201201201 Clustering
Transitivity Clustering 0.0 T=28.36611683915302 Clustering
MCODE 0.006 v=0.2
cutoff=26.519285435320466
haircut=T
fluff=T
Clustering