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 0.998 metric=euclidean
k=15
samples=20
Clustering
Self Organizing Maps 0.997 x=61
y=600
Clustering
Spectral Clustering 0.991 k=25 Clustering
clusterdp 0.999 k=17
dc=0.9295510122873538
Clustering
HDBSCAN 0.993 minPts=2
k=39
Clustering
AGNES 0.999 method=single
metric=euclidean
k=8
Clustering
c-Means 0.999 k=20
m=1.5
Clustering
k-Medoids (PAM) 0.999 k=15 Clustering
DIANA 0.995 metric=euclidean
k=10
Clustering
DBSCAN 0.997 eps=9.760285629017215
MinPts=400
Clustering
Hierarchical Clustering 0.998 method=complete
k=14
Clustering
fanny 0.998 k=18
membexp=2.0
Clustering
k-Means 0.995 k=18
nstart=10
Clustering
DensityCut 0.999 alpha=0.19047619047619047
K=29
Clustering
clusterONE 0.065 s=300
d=0.16666666666666666
Clustering
Affinity Propagation 0.999 dampfact=0.7725
preference=3.485816296077577
maxits=5000
convits=425
Clustering
Markov Clustering 0.065 I=2.3383383383383385 Clustering
Transitivity Clustering 0.999 T=12.547542943638605 Clustering
MCODE 0.993 v=0.4
cutoff=12.781326418951116
haircut=T
fluff=F
Clustering