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=281
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=188
k=563
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=77
Clustering
c-Means 0.0 k=438
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=40 Clustering
DIANA 0.0 metric=euclidean
k=581
Clustering
DBSCAN 0.0 eps=3.881546083714581
MinPts=630
Clustering
Hierarchical Clustering 0.0 method=single
k=255
Clustering
fanny 0.0 k=198
membexp=1.1
Clustering
k-Means 0.0 k=429
nstart=10
Clustering
DensityCut 0.0 alpha=0.00234375
K=13
Clustering
clusterONE 0.783 s=27
d=0.8333333333333334
Clustering
Affinity Propagation 0.002 dampfact=0.7
preference=9.703865209286453
maxits=2750
convits=500
Clustering
Markov Clustering 0.783 I=1.6612612612612614 Clustering
Transitivity Clustering 0.0 T=37.80524864318606 Clustering
MCODE 0.001 v=0.9
cutoff=35.58083910071699
haircut=T
fluff=F
Clustering