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=729
samples=20
Clustering
Self Organizing Maps 0.0 x=788
y=604
Clustering
Spectral Clustering 0.006 k=62 Clustering
clusterdp 0.0 k=11
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=8
k=105
Clustering
AGNES 0.0 method=single
metric=euclidean
k=129
Clustering
c-Means 0.0 k=788
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=582 Clustering
DIANA 0.0 metric=euclidean
k=401
Clustering
DBSCAN 0.0 eps=5.175394778286108
MinPts=604
Clustering
Hierarchical Clustering 0.0 method=complete
k=669
Clustering
fanny 0.0 k=210
membexp=5.0
Clustering
k-Means 0.0 k=592
nstart=10
Clustering
DensityCut 0.0 alpha=1.52587890625E-5
K=10
Clustering
clusterONE 0.783 s=394
d=0.23333333333333334
Clustering
Affinity Propagation 0.002 dampfact=0.7725
preference=9.703865209286453
maxits=2750
convits=500
Clustering
Markov Clustering 0.783 I=4.663563563563563 Clustering
Transitivity Clustering 0.0 T=38.349209055318234 Clustering
MCODE 0.001 v=0.8
cutoff=35.58083910071699
haircut=F
fluff=F
Clustering