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=74
samples=20
Clustering
Self Organizing Maps 0.0 x=312
y=249
Clustering
Spectral Clustering 0.0 k=25 Clustering
clusterdp 0.0 k=2
dc=23.235945333804597
Clustering
HDBSCAN 0.0 minPts=6
k=46
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=293
Clustering
c-Means 0.0 k=88
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=160 Clustering
DIANA 0.0 metric=euclidean
k=232
Clustering
DBSCAN 0.0 eps=1.010258492774113
MinPts=11
Clustering
Hierarchical Clustering 0.0 method=average
k=301
Clustering
fanny 0.0 k=89
membexp=1.1
Clustering
k-Means 0.0 k=43
nstart=10
Clustering
DensityCut 0.0 alpha=0.06696428571428571
K=6
Clustering
clusterONE 0.669 s=270
d=0.06666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=22.73081608741754
maxits=5000
convits=350
Clustering
Markov Clustering 0.669 I=4.1913913913913925 Clustering
Transitivity Clustering 0.0 T=30.06505004021459 Clustering
MCODE 0.006 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=T
Clustering