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 3.732 metric=euclidean
k=53
samples=20
Clustering
Self Organizing Maps 3.59 x=2
y=27
Clustering
Spectral Clustering 3.598 k=5 Clustering
clusterdp 3.936 k=25
dc=2.587697389143054
Clustering
HDBSCAN Infinity minPts=713
k=788
Clustering
AGNES Infinity method=flexible
metric=euclidean
k=788
Clustering
c-Means Infinity k=462
m=5.0
Clustering
k-Medoids (PAM) 3.789 k=4 Clustering
DIANA Infinity metric=euclidean
k=786
Clustering
DBSCAN Infinity eps=0.0
MinPts=525
Clustering
Hierarchical Clustering Infinity method=complete
k=788
Clustering
fanny Infinity k=196
membexp=5.0
Clustering
k-Means 3.829 k=4
nstart=10
Clustering
DensityCut 3.729 alpha=0.5714285714285714
K=75
Clustering
clusterONE -Infinity s=27
d=0.8333333333333334
Clustering
Affinity Propagation Infinity dampfact=0.9175
preference=38.815460837145814
maxits=2750
convits=425
Clustering
Markov Clustering -Infinity I=1.6612612612612614 Clustering
Transitivity Clustering Infinity T=38.815460837145814 Clustering
MCODE 1.678 v=0.3
cutoff=30.728906496073773
haircut=F
fluff=F
Clustering