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 0.0 metric=euclidean
k=197
samples=20
Clustering
Self Organizing Maps 0.0 x=61
y=153
Clustering
Spectral Clustering 0.005 k=110 Clustering
clusterdp 0.043 k=3
dc=4.856014153958941
Clustering
HDBSCAN 0.0 minPts=67
k=200
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=197
Clustering
c-Means 0.0 k=136
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=199 Clustering
DIANA 0.0 metric=euclidean
k=200
Clustering
DBSCAN 0.0 eps=0.6070017692448676
MinPts=34
Clustering
Hierarchical Clustering 0.0 method=average
k=199
Clustering
fanny 0.0 k=68
membexp=7.033333333333333
Clustering
k-Means 0.0 k=198
nstart=10
Clustering
DensityCut 0.733 alpha=0.4583333333333333
K=3
Clustering
clusterONE 0.02 s=4
d=0.6666666666666666
Clustering
Markov Clustering 1.0 I=3.87957957957958 Clustering
Transitivity Clustering 0.0 T=7.9293023910365585 Clustering
MCODE 0.063 v=0.2
cutoff=4.552513269336507
haircut=F
fluff=T
Clustering