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=3
samples=20
Clustering
Self Organizing Maps 1.0 x=2
y=1
Clustering
Spectral Clustering 1.0 k=6 Clustering
clusterdp 1.0 k=3
dc=3.6781585066443236
Clustering
HDBSCAN 1.0 minPts=253
k=1
Clustering
AGNES 1.0 method=ward
metric=euclidean
k=1
Clustering
c-Means 1.0 k=2
m=1.01
Clustering
k-Medoids (PAM) 1.0 k=2 Clustering
DIANA 1.0 metric=euclidean
k=1
Clustering
DBSCAN 1.0 eps=1.2260528355481077
MinPts=1
Clustering
Hierarchical Clustering 1.0 method=single
k=4
Clustering
fanny 1.0 k=2
membexp=1.1
Clustering
k-Means 1.0 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.8095238095238095
K=38
Clustering
clusterONE 1.0 s=27
d=0.8666666666666667
Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 1.0 I=3.1757757757757763 Clustering
Transitivity Clustering 1.0 T=0.36818403469913147 Clustering
MCODE 0.816 v=0.9
cutoff=29.11875484426756
haircut=F
fluff=F
Clustering