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 0.833 metric=euclidean
k=9
samples=20
Clustering
Self Organizing Maps 0.504 x=2
y=1
Clustering
Spectral Clustering 0.591 k=2 Clustering
clusterdp 1.0 k=6
dc=3.3120000000000003
Clustering
HDBSCAN 1.0 minPts=6
k=2
Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=5
Clustering
c-Means 0.504 k=2
m=1.01
Clustering
k-Medoids (PAM) 0.504 k=2 Clustering
DIANA 0.833 metric=euclidean
k=1
Clustering
DBSCAN 1.0 eps=3.0912
MinPts=175
Clustering
Hierarchical Clustering 1.0 method=average
k=2
Clustering
fanny 0.833 k=2
membexp=1.1
Clustering
k-Means 0.503 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.1125
K=3
Clustering
clusterONE 0.833 s=25
d=0.5
Clustering
Affinity Propagation 0.833 dampfact=0.9175
preference=2.484
maxits=3500
convits=500
Clustering
Markov Clustering 0.833 I=3.3450450450450453 Clustering
Transitivity Clustering 0.833 T=0.09614414414414414 Clustering
MCODE 0.761 v=0.3
cutoff=1.2420000000000002
haircut=F
fluff=F
Clustering