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=66
samples=20
Clustering
Self Organizing Maps 0.0 x=84
y=9
Clustering
Spectral Clustering 0.0 k=83 Clustering
clusterdp 0.0 k=17
dc=0.11040000000000001
Clustering
HDBSCAN 0.0 minPts=72
k=250
Clustering
AGNES 0.0 method=average
metric=euclidean
k=98
Clustering
c-Means 0.0 k=197
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=77 Clustering
DIANA 0.0 metric=euclidean
k=80
Clustering
DBSCAN 0.0 eps=0.11040000000000001
MinPts=9
Clustering
Hierarchical Clustering 0.0 method=single
k=122
Clustering
fanny 0.0 k=117
membexp=2.0
Clustering
k-Means 0.0 k=225
nstart=10
Clustering
DensityCut 0.0 alpha=0.04709821428571427
K=3
Clustering
clusterONE 1.0 s=175
d=0.6
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=3.3120000000000003
maxits=2750
convits=500
Clustering
Markov Clustering 0.5 I=8.432032032032032 Clustering
Transitivity Clustering 0.0 T=3.09318918918919 Clustering
MCODE 0.001 v=0.9
cutoff=3.036
haircut=F
fluff=F
Clustering