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=37
samples=20
Clustering
Self Organizing Maps 0.0 x=3
y=28
Clustering
Spectral Clustering 0.423 k=33 Clustering
clusterdp 0.0 k=20
dc=0.2237311883923943
Clustering
HDBSCAN 0.0 minPts=4
k=23
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=28
Clustering
c-Means 0.0 k=22
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=33 Clustering
DIANA 0.0 metric=euclidean
k=34
Clustering
DBSCAN 0.0 eps=0.0
MinPts=4
Clustering
Hierarchical Clustering 0.0 method=average
k=33
Clustering
fanny 0.007 k=17
membexp=1.1
Clustering
k-Means 0.0 k=37
nstart=10
Clustering
DensityCut 0.15 alpha=0.7071428571428572
K=2
Clustering
clusterONE 0.057 s=4
d=0.8666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=0.6101759683428936
maxits=4250
convits=350
Clustering
Markov Clustering 0.341 I=9.91981981981982 Clustering
Transitivity Clustering 0.0 T=0.5930739392001497 Clustering