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=519
samples=20
Clustering
Self Organizing Maps 0.0 x=600
y=540
Clustering
Spectral Clustering 0.013 k=39 Clustering
clusterdp 0.003 k=17
dc=0.9295510122873538
Clustering
HDBSCAN 0.0 minPts=24
k=201
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=541
Clustering
c-Means 0.0 k=593
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=528 Clustering
DIANA 0.0 metric=euclidean
k=487
Clustering
DBSCAN 0.0 eps=0.4647755061436769
MinPts=280
Clustering
Hierarchical Clustering 0.0 method=single
k=540
Clustering
fanny 0.0 k=273
membexp=2.0
Clustering
k-Means 0.0 k=428
nstart=10
Clustering
DensityCut 0.007 alpha=0.47619047619047616
K=29
Clustering
clusterONE 0.935 s=580
d=0.6
Clustering
Affinity Propagation 0.004 dampfact=0.7725
preference=10.457448888232731
maxits=2000
convits=350
Clustering
Markov Clustering 0.935 I=5.937537537537538 Clustering
Transitivity Clustering 0.0 T=13.873479072276723 Clustering
MCODE 0.017 v=0.8
cutoff=12.781326418951116
haircut=T
fluff=F
Clustering