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=18
y=36
Clustering
Spectral Clustering 0.423 k=33 Clustering
clusterdp 0.0 k=22
dc=0.18305279050286807
Clustering
HDBSCAN 0.0 minPts=4
k=32
Clustering
AGNES 0.0 method=average
metric=euclidean
k=30
Clustering
c-Means 0.0 k=6
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=36 Clustering
DIANA 0.0 metric=euclidean
k=37
Clustering
DBSCAN 0.0 eps=0.0
MinPts=4
Clustering
Hierarchical Clustering 0.0 method=complete
k=36
Clustering
fanny 0.007 k=18
membexp=1.1
Clustering
k-Means 0.0 k=34
nstart=10
Clustering
DensityCut 0.15 alpha=0.7619047619047619
K=2
Clustering
clusterONE 0.057 s=1
d=0.8666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=0.6101759683428936
maxits=4250
convits=200
Clustering
Markov Clustering 0.341 I=9.884184184184184 Clustering
Transitivity Clustering 0.0 T=0.5124500875272149 Clustering