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=470
samples=20
Clustering
Self Organizing Maps 0.0 x=600
y=540
Clustering
Spectral Clustering 0.0 k=100 Clustering
clusterdp 0.0 k=22
dc=0.9295510122873538
Clustering
HDBSCAN 0.0 minPts=10
k=93
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=446
Clustering
c-Means 0.0 k=62
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=478 Clustering
DIANA 0.0 metric=euclidean
k=477
Clustering
DBSCAN 0.0 eps=0.9295510122873538
MinPts=120
Clustering
Hierarchical Clustering 0.0 method=complete
k=547
Clustering
fanny 0.0 k=263
membexp=1.1
Clustering
k-Means 0.0 k=484
nstart=10
Clustering
DensityCut 0.0 alpha=0.3976190476190476
K=24
Clustering
clusterONE 1.0 s=60
d=0.43333333333333335
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=10.457448888232731
maxits=5000
convits=500
Clustering
Markov Clustering 1.0 I=8.503303303303305 Clustering
Transitivity Clustering 0.0 T=13.88743629468344 Clustering
MCODE 0.001 v=0.9
cutoff=13.36229580163071
haircut=T
fluff=F
Clustering