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=220
samples=20
Clustering
Self Organizing Maps 0.0 x=68
y=42
Clustering
Spectral Clustering 0.0 k=17 Clustering
clusterdp 0.0 k=23
dc=2.480263878770637
Clustering
HDBSCAN 0.0 minPts=1
k=214
Clustering
AGNES 0.0 method=average
metric=euclidean
k=33
Clustering
c-Means 0.0 k=51
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=180 Clustering
DIANA 0.0 metric=euclidean
k=74
Clustering
DBSCAN 0.0 eps=1.5664824497498762
MinPts=225
Clustering
Hierarchical Clustering 0.0 method=single
k=118
Clustering
fanny 0.0 k=89
membexp=1.1
Clustering
k-Means 0.0 k=31
nstart=10
Clustering
DensityCut 0.0 alpha=0.9625
K=6
Clustering
clusterONE 1.0 s=133
d=1.0
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=2.9371545932810177
maxits=5000
convits=275
Clustering
Markov Clustering 1.0 I=6.374074074074075 Clustering
Transitivity Clustering 0.0 T=3.9162061243746904 Clustering
MCODE 0.001 v=0.9
cutoff=3.589855614010133
haircut=T
fluff=T
Clustering