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=149
samples=20
Clustering
Self Organizing Maps 0.0 x=68
y=233
Clustering
Spectral Clustering 0.0 k=77 Clustering
clusterdp 0.0 k=4
dc=0.7728
Clustering
HDBSCAN 0.0 minPts=7
k=25
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=46
Clustering
c-Means 0.0 k=172
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=66 Clustering
DIANA 0.0 metric=euclidean
k=196
Clustering
DBSCAN 0.0 eps=2.6496
MinPts=158
Clustering
Hierarchical Clustering 0.0 method=average
k=125
Clustering
fanny 0.0 k=112
membexp=2.0
Clustering
k-Means 0.0 k=177
nstart=10
Clustering
DensityCut 0.0 alpha=0.024330357142857133
K=3
Clustering
clusterONE 0.502 s=241
d=0.9
Clustering
Affinity Propagation 0.062 dampfact=0.9175
preference=2.484
maxits=4250
convits=500
Clustering
Markov Clustering 0.502 I=4.877377377377377 Clustering
Transitivity Clustering 0.0 T=3.1661261261261266 Clustering
MCODE 0.021 v=0.6
cutoff=3.036
haircut=F
fluff=T
Clustering