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 2.367 metric=euclidean
k=2
samples=20
Clustering
Self Organizing Maps 2.285 x=2
y=2
Clustering
Spectral Clustering 2.687 k=2 Clustering
clusterdp Infinity k=34
dc=0.08135679577905247
Clustering
HDBSCAN Infinity minPts=27
k=38
Clustering
AGNES 2.702 method=complete
metric=euclidean
k=3
Clustering
c-Means NaN k=3
m=3.5
Clustering
k-Medoids (PAM) 2.885 k=4 Clustering
DIANA NaN metric=euclidean
k=10
Clustering
DBSCAN Infinity eps=0.0
MinPts=35
Clustering
Hierarchical Clustering 2.887 method=single
k=2
Clustering
fanny 2.687 k=2
membexp=2.0
Clustering
k-Means 2.687 k=8
nstart=10
Clustering
DensityCut 2.519 alpha=0.43333333333333335
K=2
Clustering
clusterONE -Infinity s=1
d=0.8666666666666667
Clustering
Affinity Propagation 2.788 dampfact=0.7
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering -Infinity I=1.1623623623623625 Clustering
Transitivity Clustering Infinity T=0.5613130279350542 Clustering
MCODE -Infinity v=0.0
cutoff=0.0
haircut=T
fluff=T
Clustering