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 0.88 metric=euclidean
k=53
samples=20
Clustering
Self Organizing Maps 0.72 x=2
y=27
Clustering
Spectral Clustering 0.962 k=9 Clustering
clusterdp 1.0 k=8
dc=2.587697389143054
Clustering
HDBSCAN 0.905 minPts=8
k=95
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=4
Clustering
c-Means 0.918 k=8
m=3.5
Clustering
k-Medoids (PAM) 0.876 k=4 Clustering
DIANA 0.879 metric=euclidean
k=3
Clustering
DBSCAN 0.916 eps=36.22776344800276
MinPts=499
Clustering
Hierarchical Clustering 0.982 method=single
k=6
Clustering
fanny 0.887 k=4
membexp=5.0
Clustering
k-Means 0.889 k=6
nstart=10
Clustering
DensityCut 1.0 alpha=0.00234375
K=13
Clustering
clusterONE 0.543 s=27
d=0.8333333333333334
Clustering
Affinity Propagation 0.543 dampfact=0.845
preference=9.703865209286453
maxits=5000
convits=500
Clustering
Markov Clustering 0.543 I=1.6612612612612614 Clustering
Transitivity Clustering 0.984 T=28.713338897548304 Clustering
MCODE 0.833 v=0.7
cutoff=30.728906496073773
haircut=F
fluff=T
Clustering