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 0.638 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.638 x=2
y=1
Clustering
Spectral Clustering 0.638 k=6 Clustering
clusterdp 0.638 k=2
dc=9.808422684384862
Clustering
HDBSCAN 0.255 minPts=4
k=50
Clustering
AGNES 0.55 method=weighted
metric=euclidean
k=4
Clustering
c-Means 0.638 k=2
m=1.01
Clustering
k-Medoids (PAM) 0.638 k=2 Clustering
DIANA 0.638 metric=euclidean
k=1
Clustering
DBSCAN 0.638 eps=34.329479395347015
MinPts=319
Clustering
Hierarchical Clustering 0.638 method=average
k=2
Clustering
fanny 0.638 k=2
membexp=1.1
Clustering
k-Means 0.638 k=2
nstart=10
Clustering
DensityCut 0.638 alpha=0.8095238095238095
K=38
Clustering
clusterONE NaN s=27
d=0.8666666666666667
Clustering
Affinity Propagation 0.421 dampfact=0.99
preference=9.195396266610809
maxits=2750
convits=200
Clustering
Markov Clustering NaN I=3.1757757757757763 Clustering
Transitivity Clustering 0.638 T=21.906950064598323 Clustering
MCODE 0.336 v=0.9
cutoff=29.11875484426756
haircut=F
fluff=F
Clustering