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=195
samples=20
Clustering
Self Organizing Maps 0.0 x=200
y=180
Clustering
Spectral Clustering 0.004 k=59 Clustering
clusterdp 0.022 k=5
dc=4.895619710727704
Clustering
HDBSCAN 0.0 minPts=133
k=200
Clustering
AGNES 0.0 method=single
metric=euclidean
k=200
Clustering
c-Means 0.0 k=186
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=194 Clustering
DIANA 0.0 metric=euclidean
k=184
Clustering
DBSCAN 0.0 eps=0.9791239421455409
MinPts=54
Clustering
Hierarchical Clustering 0.0 method=single
k=179
Clustering
fanny 0.0 k=48
membexp=7.923333333333334
Clustering
k-Means 0.0 k=193
nstart=10
Clustering
DensityCut 0.083 alpha=0.0
K=2
Clustering
clusterONE 0.006 s=5
d=0.7
Clustering
Markov Clustering 1.0 I=4.61011011011011 Clustering
Transitivity Clustering 0.0 T=12.922671849037995 Clustering
MCODE 0.052 v=0.1
cutoff=4.895619710727704
haircut=T
fluff=F
Clustering