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 0.441 metric=euclidean
k=11
samples=20
Clustering
Self Organizing Maps 0.378 x=2
y=1
Clustering
Spectral Clustering 0.414 k=6 Clustering
clusterdp 0.382 k=4
dc=0.9838981428763629
Clustering
HDBSCAN -0.009 minPts=240
k=232
Clustering
AGNES 0.438 method=ward
metric=euclidean
k=6
Clustering
c-Means 0.443 k=3
m=5.0
Clustering
k-Medoids (PAM) 0.439 k=4 Clustering
DIANA 0.434 metric=euclidean
k=5
Clustering
DBSCAN 0.295 eps=12.298726785954536
MinPts=176
Clustering
Hierarchical Clustering 0.438 method=average
k=4
Clustering
fanny 0.444 k=3
membexp=5.0
Clustering
k-Means 0.443 k=4
nstart=10
Clustering
DensityCut 0.334 alpha=1.0
K=12
Clustering
clusterONE NaN s=8
d=0.9
Clustering
Affinity Propagation 0.35 dampfact=0.99
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering NaN I=1.1356356356356356 Clustering
Transitivity Clustering 0.426 T=10.326498526585251 Clustering
MCODE -0.001 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T
Clustering