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 0.576 metric=euclidean
k=1
samples=20
Clustering
Self Organizing Maps 0.404 x=2
y=1
Clustering
Spectral Clustering 0.924 k=3 Clustering
clusterdp 1.0 k=3
dc=14.14361889883758
Clustering
HDBSCAN 0.901 minPts=5
k=34
Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=3
Clustering
c-Means 0.404 k=7
m=2.25
Clustering
k-Medoids (PAM) 0.406 k=13 Clustering
DIANA 0.576 metric=euclidean
k=4
Clustering
DBSCAN 1.0 eps=14.14361889883758
MinPts=280
Clustering
Hierarchical Clustering 1.0 method=complete
k=3
Clustering
fanny 0.576 k=8
membexp=2.0
Clustering
k-Means 0.404 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.07387329931972789
K=6
Clustering
clusterONE 0.576 s=52
d=0.9666666666666667
Clustering
Affinity Propagation 0.576 dampfact=0.9175
preference=7.576938695805847
maxits=3500
convits=200
Clustering
Markov Clustering 0.576 I=6.73933933933934 Clustering
Transitivity Clustering 0.576 T=11.467799107165607 Clustering
MCODE 0.415 v=0.4
cutoff=17.679523623546974
haircut=T
fluff=T
Clustering