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 0.318 metric=euclidean
k=200
samples=20
Clustering
Self Organizing Maps 0.662 x=200
y=180
Clustering
Spectral Clustering 0.922 k=25 Clustering
clusterdp 0.432 k=2
dc=0.0
Clustering
HDBSCAN 0.0 minPts=27
k=200
Clustering
AGNES 0.0 method=average
metric=euclidean
k=200
Clustering
c-Means 0.0 k=80
m=5.0
Clustering
k-Medoids (PAM) 0.318 k=199 Clustering
DIANA 0.0 metric=euclidean
k=200
Clustering
DBSCAN 0.0 eps=1.4686859132183112
MinPts=47
Clustering
Hierarchical Clustering 0.0 method=complete
k=199
Clustering
fanny 0.0 k=68
membexp=4.363333333333333
Clustering
k-Means 0.348 k=198
nstart=10
Clustering
DensityCut 0.968 alpha=0.0
K=2
Clustering
clusterONE 0.774 s=14
d=0.7
Clustering
Markov Clustering Infinity I=1.2336336336336338 Clustering
Transitivity Clustering 0.0 T=9.026758265425858 Clustering
MCODE 0.87 v=0.4
cutoff=7.955382029932519
haircut=F
fluff=T
Clustering