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=85
samples=20
Clustering
Self Organizing Maps 0.0 x=73
y=208
Clustering
Spectral Clustering 0.005 k=8 Clustering
clusterdp 0.0 k=10
dc=5.903388857258178
Clustering
HDBSCAN 0.0 minPts=24
k=216
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=24
Clustering
c-Means 0.0 k=203
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=175 Clustering
DIANA 0.0 metric=euclidean
k=238
Clustering
DBSCAN 0.0 eps=7.871185143010903
MinPts=168
Clustering
Hierarchical Clustering 0.0 method=average
k=129
Clustering
fanny 0.0 k=46
membexp=2.0
Clustering
k-Means 0.0 k=76
nstart=10
Clustering
DensityCut 0.0 alpha=0.5880952380952381
K=10
Clustering
clusterONE 0.464 s=16
d=0.8
Clustering
Affinity Propagation 0.014 dampfact=0.99
preference=0.0
maxits=4250
convits=200
Clustering
Markov Clustering 0.464 I=7.247147147147147 Clustering
Transitivity Clustering 0.0 T=13.812984438279267 Clustering
MCODE 0.175 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T
Clustering