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=196
samples=20
Clustering
Self Organizing Maps 1.0 x=61
y=153
Clustering
Spectral Clustering 0.995 k=110 Clustering
clusterdp 0.957 k=3
dc=4.856014153958941
Clustering
HDBSCAN 1.0 minPts=143
k=200
Clustering
AGNES 1.0 method=ward
metric=euclidean
k=200
Clustering
c-Means 1.0 k=106
m=3.5
Clustering
k-Medoids (PAM) 1.0 k=198 Clustering
DIANA 1.0 metric=euclidean
k=200
Clustering
DBSCAN 1.0 eps=0.6070017692448676
MinPts=34
Clustering
Hierarchical Clustering 1.0 method=average
k=200
Clustering
fanny 1.0 k=21
membexp=3.176666666666667
Clustering
k-Means 1.0 k=199
nstart=10
Clustering
DensityCut 0.267 alpha=0.4583333333333333
K=3
Clustering
clusterONE 0.98 s=1
d=0.6666666666666666
Clustering
Markov Clustering 0.0 I=7.879679679679681 Clustering
Transitivity Clustering 1.0 T=8.658433645384747 Clustering
MCODE 0.937 v=0.3
cutoff=4.552513269336507
haircut=F
fluff=F
Clustering