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=324
samples=20
Clustering
Self Organizing Maps 1.0 x=385
y=239
Clustering
Spectral Clustering 0.999 k=24 Clustering
clusterdp 0.991 k=24
dc=3.6781585066443236
Clustering
HDBSCAN 1.0 minPts=1
k=304
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=195
Clustering
c-Means 1.0 k=286
m=1.5
Clustering
k-Medoids (PAM) 1.0 k=214 Clustering
DIANA 1.0 metric=euclidean
k=354
Clustering
DBSCAN 1.0 eps=2.4521056710962155
MinPts=372
Clustering
Hierarchical Clustering 1.0 method=single
k=238
Clustering
fanny 1.0 k=204
membexp=2.0
Clustering
k-Means 1.0 k=263
nstart=10
Clustering
DensityCut 0.935 alpha=0.13215702947845803
K=3
Clustering
clusterONE 0.0 s=292
d=0.4
Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=36.781585066443235
maxits=5000
convits=500
Clustering
Markov Clustering 0.0 I=6.525525525525525 Clustering
Transitivity Clustering 1.0 T=36.560674645623756 Clustering
MCODE 0.996 v=0.1
cutoff=32.183886933137835
haircut=F
fluff=T
Clustering