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 1.0 metric=euclidean
k=1
samples=20
Clustering
Self Organizing Maps 0.979 x=2
y=27
Clustering
Spectral Clustering 1.0 k=5 Clustering
clusterdp 1.0 k=4
dc=34.93391475343124
Clustering
HDBSCAN 1.0 minPts=158
k=1
Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=6
Clustering
c-Means 0.993 k=3
m=1.01
Clustering
k-Medoids (PAM) 0.995 k=2 Clustering
DIANA 1.0 metric=euclidean
k=2
Clustering
DBSCAN 1.0 eps=0.0
MinPts=420
Clustering
Hierarchical Clustering 1.0 method=complete
k=6
Clustering
fanny 1.0 k=2
membexp=5.0
Clustering
k-Means 0.993 k=3
nstart=10
Clustering
DensityCut 1.0 alpha=0.38095238095238093
K=75
Clustering
clusterONE 1.0 s=27
d=0.8333333333333334
Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=9.703865209286453
maxits=5000
convits=500
Clustering
Markov Clustering 1.0 I=1.6612612612612614 Clustering
Transitivity Clustering 1.0 T=6.838359466804468 Clustering
MCODE 0.818 v=0.0
cutoff=35.58083910071699
haircut=T
fluff=T
Clustering