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=211
samples=20
Clustering
Self Organizing Maps 0.0 x=300
y=220
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=21
dc=0.9765301383526837
Clustering
HDBSCAN 0.0 minPts=160
k=260
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=110
Clustering
c-Means 0.0 k=260
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=169 Clustering
DIANA 0.0 metric=euclidean
k=278
Clustering
DBSCAN 0.0 eps=13.671421936937572
MinPts=230
Clustering
Hierarchical Clustering 0.0 method=average
k=295
Clustering
fanny 0.0 k=99
membexp=5.0
Clustering
k-Means 0.0 k=298
nstart=10
Clustering
DensityCut 0.005 alpha=0.06914682539682541
K=2
Clustering
clusterONE 0.667 s=270
d=0.9333333333333333
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=29.29590415058051
maxits=4250
convits=200
Clustering
Markov Clustering 0.471 I=9.233833833833835 Clustering
Transitivity Clustering 0.0 T=27.800317452202524 Clustering