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=217
samples=20
Clustering
Self Organizing Maps 0.0 x=2
y=191
Clustering
Spectral Clustering 0.0 k=2 Clustering
clusterdp 0.0 k=17
dc=0.44160000000000005
Clustering
HDBSCAN 0.0 minPts=4
k=10
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=44
Clustering
c-Means 0.0 k=169
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=68 Clustering
DIANA 0.0 metric=euclidean
k=132
Clustering
DBSCAN 0.0 eps=2.8704000000000005
MinPts=216
Clustering
Hierarchical Clustering 0.0 method=single
k=201
Clustering
fanny 0.0 k=65
membexp=2.0
Clustering
k-Means 0.0 k=193
nstart=10
Clustering
DensityCut 0.0 alpha=0.0
K=3
Clustering
clusterONE 1.0 s=133
d=0.36666666666666664
Clustering
Affinity Propagation 0.0 dampfact=0.7
preference=3.3120000000000003
maxits=5000
convits=350
Clustering
Markov Clustering 0.5 I=9.233833833833835 Clustering
Transitivity Clustering 0.0 T=3.139603603603604 Clustering
MCODE 0.001 v=0.6
cutoff=3.036
haircut=T
fluff=T
Clustering