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 0.02 metric=euclidean
k=399
samples=20
Clustering
Self Organizing Maps 0.337 x=2
y=1
Clustering
Spectral Clustering 0.337 k=6 Clustering
clusterdp 0.334 k=22
dc=0.0
Clustering
HDBSCAN 0.0 minPts=266
k=399
Clustering
AGNES 0.0 method=average
metric=euclidean
k=399
Clustering
c-Means 0.0 k=230
m=3.5
Clustering
k-Medoids (PAM) 0.02 k=398 Clustering
DIANA 0.0 metric=euclidean
k=397
Clustering
DBSCAN 0.0 eps=0.0
MinPts=133
Clustering
Hierarchical Clustering 0.0 method=single
k=397
Clustering
fanny 0.0 k=161
membexp=2.0
Clustering
k-Means 0.032 k=398
nstart=10
Clustering
DensityCut 0.337 alpha=0.8095238095238095
K=38
Clustering
clusterONE Infinity s=27
d=0.8666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=36.781585066443235
maxits=2000
convits=500
Clustering
Markov Clustering Infinity I=3.1757757757757763 Clustering
Transitivity Clustering 0.0 T=36.781585066443235 Clustering
MCODE 0.541 v=0.8
cutoff=29.11875484426756
haircut=T
fluff=T
Clustering