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 1.0 metric=euclidean
k=1
samples=20
Clustering
Self Organizing Maps 0.987 x=2
y=1
Clustering
Spectral Clustering 1.0 k=17 Clustering
clusterdp 1.0 k=7
dc=5.577306073724123
Clustering
HDBSCAN 1.0 minPts=229
k=1
Clustering
AGNES 1.0 method=complete
metric=euclidean
k=5
Clustering
c-Means 1.0 k=2
m=1.5
Clustering
k-Medoids (PAM) 1.0 k=2 Clustering
DIANA 1.0 metric=euclidean
k=19
Clustering
DBSCAN 1.0 eps=4.182979555293092
MinPts=220
Clustering
Hierarchical Clustering 1.0 method=complete
k=3
Clustering
fanny 1.0 k=2
membexp=5.0
Clustering
k-Means 1.0 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.1976190476190476
K=95
Clustering
clusterONE 1.0 s=240
d=0.1
Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=0.0
maxits=2750
convits=500
Clustering
Markov Clustering 1.0 I=4.066666666666667 Clustering
Transitivity Clustering 1.0 T=0.15352944647388728 Clustering
MCODE 0.909 v=0.6
cutoff=12.781326418951116
haircut=T
fluff=F
Clustering