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=30
samples=20
Clustering
Self Organizing Maps 0.0 x=38
y=38
Clustering
Spectral Clustering 0.423 k=33 Clustering
clusterdp 0.0 k=3
dc=0.2847487852266836
Clustering
HDBSCAN 0.0 minPts=27
k=34
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=26
Clustering
c-Means 0.0 k=32
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=35 Clustering
DIANA 0.0 metric=euclidean
k=33
Clustering
DBSCAN 0.0 eps=0.16271359155810494
MinPts=5
Clustering
Hierarchical Clustering 0.0 method=single
k=31
Clustering
fanny 0.007 k=18
membexp=1.1
Clustering
k-Means 0.0 k=32
nstart=10
Clustering
DensityCut 0.15 alpha=0.7558035714285714
K=2
Clustering
clusterONE 0.057 s=5
d=0.8
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=0.6101759683428936
maxits=2000
convits=350
Clustering
Markov Clustering 0.341 I=9.93763763763764 Clustering
Transitivity Clustering 0.0 T=0.4922941246089812 Clustering