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=28
y=38
Clustering
Spectral Clustering 0.423 k=33 Clustering
clusterdp 0.0 k=2
dc=0.3050879841714468
Clustering
HDBSCAN 0.0 minPts=8
k=29
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=29
Clustering
c-Means 0.0 k=3
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=35 Clustering
DIANA 0.0 metric=euclidean
k=38
Clustering
DBSCAN 0.0 eps=0.08135679577905247
MinPts=38
Clustering
Hierarchical Clustering 0.0 method=average
k=33
Clustering
fanny 0.007 k=16
membexp=1.1
Clustering
k-Means 0.0 k=31
nstart=10
Clustering
DensityCut 0.15 alpha=0.8698412698412699
K=2
Clustering
clusterONE 0.057 s=2
d=0.8666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=0.6101759683428936
maxits=2000
convits=275
Clustering
Markov Clustering 0.341 I=9.928728728728728 Clustering
Transitivity Clustering 0.0 T=0.502066712690549 Clustering