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=710
samples=20
Clustering
Self Organizing Maps 0.0 x=788
y=604
Clustering
Spectral Clustering 0.006 k=62 Clustering
clusterdp 0.0 k=17
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=53
k=368
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=384
Clustering
c-Means 0.0 k=740
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=632 Clustering
DIANA 0.0 metric=euclidean
k=401
Clustering
DBSCAN 0.0 eps=5.175394778286108
MinPts=604
Clustering
Hierarchical Clustering 0.0 method=average
k=563
Clustering
fanny 0.0 k=212
membexp=1.1
Clustering
k-Means 0.0 k=444
nstart=10
Clustering
DensityCut 0.0 alpha=0.0
K=13
Clustering
clusterONE 0.783 s=551
d=0.7
Clustering
Affinity Propagation 0.002 dampfact=0.99
preference=0.0
maxits=5000
convits=425
Clustering
Markov Clustering 0.783 I=4.725925925925926 Clustering
Transitivity Clustering 0.0 T=38.504626315927425 Clustering
MCODE 0.001 v=0.8
cutoff=35.58083910071699
haircut=F
fluff=F
Clustering