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 0.993 metric=euclidean
k=16
samples=20
Clustering
Self Organizing Maps 0.98 x=61
y=600
Clustering
Spectral Clustering 0.952 k=25 Clustering
clusterdp 0.997 k=15
dc=0.4647755061436769
Clustering
HDBSCAN 0.973 minPts=2
k=39
Clustering
AGNES 0.995 method=single
metric=euclidean
k=8
Clustering
c-Means 0.997 k=20
m=1.5
Clustering
k-Medoids (PAM) 0.997 k=15 Clustering
DIANA 0.979 metric=euclidean
k=13
Clustering
DBSCAN 0.989 eps=9.760285629017215
MinPts=400
Clustering
Hierarchical Clustering 0.994 method=complete
k=14
Clustering
fanny 0.989 k=18
membexp=2.0
Clustering
k-Means 0.974 k=18
nstart=10
Clustering
DensityCut 0.997 alpha=0.31845238095238093
K=16
Clustering
clusterONE 0.125 s=260
d=0.16666666666666666
Clustering
Affinity Propagation 0.997 dampfact=0.9175
preference=3.485816296077577
maxits=4250
convits=275
Clustering
Markov Clustering 0.125 I=4.85955955955956 Clustering
Transitivity Clustering 0.997 T=12.659200722892342 Clustering
MCODE 0.969 v=0.1
cutoff=12.781326418951116
haircut=T
fluff=T
Clustering