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=92
samples=20
Clustering
Self Organizing Maps 0.0 x=43
y=225
Clustering
Spectral Clustering 0.0 k=9 Clustering
clusterdp 0.0 k=17
dc=1.3248
Clustering
HDBSCAN 0.0 minPts=1
k=29
Clustering
AGNES 0.0 method=single
metric=euclidean
k=62
Clustering
c-Means 0.0 k=119
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=149 Clustering
DIANA 0.0 metric=euclidean
k=78
Clustering
DBSCAN 0.0 eps=0.552
MinPts=17
Clustering
Hierarchical Clustering 0.0 method=complete
k=60
Clustering
fanny 0.0 k=97
membexp=1.1
Clustering
k-Means 0.0 k=106
nstart=10
Clustering
DensityCut 0.0 alpha=0.07589285714285712
K=4
Clustering
clusterONE 0.502 s=92
d=0.9
Clustering
Affinity Propagation 0.062 dampfact=0.9175
preference=2.484
maxits=4250
convits=500
Clustering
Markov Clustering 0.502 I=2.953053053053053 Clustering
Transitivity Clustering 0.0 T=3.2258018018018024 Clustering
MCODE 0.021 v=0.9
cutoff=3.036
haircut=T
fluff=T
Clustering