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 0.258 metric=euclidean
k=38
samples=20
Clustering
Self Organizing Maps 0.665 x=2
y=2
Clustering
Spectral Clustering 0.593 k=2 Clustering
clusterdp 0.0 k=34
dc=0.08135679577905247
Clustering
HDBSCAN 0.0 minPts=27
k=38
Clustering
AGNES 0.433 method=flexible
metric=euclidean
k=2
Clustering
c-Means NaN k=3
m=3.5
Clustering
k-Medoids (PAM) 0.193 k=37 Clustering
DIANA NaN metric=euclidean
k=10
Clustering
DBSCAN 0.0 eps=0.0
MinPts=35
Clustering
Hierarchical Clustering 0.372 method=average
k=7
Clustering
fanny 0.414 k=2
membexp=1.1
Clustering
k-Means 0.593 k=8
nstart=10
Clustering
DensityCut 0.623 alpha=0.43333333333333335
K=2
Clustering
clusterONE Infinity s=1
d=0.3
Clustering
Affinity Propagation 0.582 dampfact=0.7725
preference=0.0
maxits=2000
convits=350
Clustering
Markov Clustering Infinity I=1.2247247247247248 Clustering
Transitivity Clustering 0.0 T=0.5613130279350542 Clustering
MCODE Infinity v=0.0
cutoff=0.0
haircut=T
fluff=T
Clustering