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=764
samples=20
Clustering
Self Organizing Maps 0.0 x=447
y=420
Clustering
Spectral Clustering 0.0 k=118 Clustering
clusterdp 0.0 k=13
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=79
k=499
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=129
Clustering
c-Means 0.0 k=660
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=558 Clustering
DIANA 0.0 metric=euclidean
k=474
Clustering
DBSCAN 0.0 eps=0.0
MinPts=525
Clustering
Hierarchical Clustering 0.0 method=single
k=773
Clustering
fanny 0.0 k=146
membexp=2.0
Clustering
k-Means 0.0 k=686
nstart=10
Clustering
DensityCut 0.0 alpha=0.0
K=13
Clustering
clusterONE 1.0 s=709
d=0.5666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=38.815460837145814
maxits=5000
convits=500
Clustering
Markov Clustering 1.0 I=8.904204204204206 Clustering
Transitivity Clustering 0.0 T=37.72754001288147 Clustering
MCODE 0.0 v=0.8
cutoff=35.58083910071699
haircut=T
fluff=T
Clustering