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=76
samples=20
Clustering
Self Organizing Maps 0.0 x=49
y=32
Clustering
Spectral Clustering 0.002 k=34 Clustering
clusterdp 0.0 k=18
dc=10.82287957163999
Clustering
HDBSCAN 0.0 minPts=240
k=136
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=172
Clustering
c-Means 0.0 k=7
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=209 Clustering
DIANA 0.0 metric=euclidean
k=119
Clustering
DBSCAN 0.0 eps=0.9838981428763629
MinPts=8
Clustering
Hierarchical Clustering 0.0 method=average
k=3
Clustering
fanny 0.0 k=98
membexp=1.1
Clustering
k-Means 0.0 k=101
nstart=10
Clustering
DensityCut 0.0 alpha=0.9523809523809523
K=12
Clustering
clusterONE 1.0 s=184
d=0.7333333333333333
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=14.758472143145443
maxits=5000
convits=350
Clustering
Markov Clustering 1.0 I=3.8528528528528527 Clustering
Transitivity Clustering 0.0 T=14.581193198483035 Clustering
MCODE 0.009 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T
Clustering