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 0.831 x=2
y=1
Clustering
Spectral Clustering 0.965 k=4 Clustering
clusterdp 0.831 k=2
dc=0.0
Clustering
HDBSCAN 0.833 minPts=140
k=7
Clustering
AGNES 0.89 method=flexible
metric=euclidean
k=1
Clustering
c-Means 0.97 k=4
m=1.01
Clustering
k-Medoids (PAM) 0.66 k=3 Clustering
DIANA 0.95 metric=euclidean
k=47
Clustering
DBSCAN 0.833 eps=0.0
MinPts=20
Clustering
Hierarchical Clustering 0.89 method=single
k=2
Clustering
fanny 0.898 k=2
membexp=1.3966666666666667
Clustering
k-Means 0.965 k=2
nstart=10
Clustering
DensityCut 0.833 alpha=0.14285714285714285
K=86
Clustering
clusterONE 0.833 s=1
d=0.06666666666666667
Clustering
Markov Clustering 0.833 I=5.9998998998999 Clustering
Transitivity Clustering 0.833 T=0.01822828135870473 Clustering
MCODE 0.833 v=0.3
cutoff=7.587522115560845
haircut=F
fluff=T
Clustering