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 0.527 metric=euclidean
k=53
samples=20
Clustering
Self Organizing Maps 0.455 x=2
y=27
Clustering
Spectral Clustering 0.48 k=9 Clustering
clusterdp 0.526 k=5
dc=29.758519975145123
Clustering
HDBSCAN 0.102 minPts=237
k=27
Clustering
AGNES 0.526 method=average
metric=euclidean
k=3
Clustering
c-Means 0.524 k=4
m=1.5
Clustering
k-Medoids (PAM) 0.526 k=4 Clustering
DIANA 0.522 metric=euclidean
k=3
Clustering
DBSCAN 0.412 eps=36.22776344800276
MinPts=499
Clustering
Hierarchical Clustering 0.523 method=complete
k=2
Clustering
fanny 0.526 k=4
membexp=1.1
Clustering
k-Means 0.524 k=4
nstart=10
Clustering
DensityCut 0.526 alpha=0.2857142857142857
K=75
Clustering
clusterONE NaN s=27
d=0.8333333333333334
Clustering
Affinity Propagation 0.405 dampfact=0.9175
preference=0.0
maxits=3500
convits=275
Clustering
Markov Clustering NaN I=1.6612612612612614 Clustering
Transitivity Clustering 0.527 T=26.304371358105822 Clustering
MCODE 0.303 v=0.7
cutoff=33.96352823250259
haircut=T
fluff=T
Clustering