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 0.538 metric=euclidean
k=50
samples=20
Clustering
Self Organizing Maps 0.599 x=2
y=140
Clustering
Spectral Clustering 0.932 k=4 Clustering
clusterdp 0.549 k=5
dc=0.0
Clustering
HDBSCAN 0.507 minPts=1
k=76
Clustering
AGNES 0.803 method=complete
metric=euclidean
k=2
Clustering
c-Means 0.942 k=30
m=1.01
Clustering
k-Medoids (PAM) 0.549 k=3 Clustering
DIANA 0.905 metric=euclidean
k=1
Clustering
DBSCAN 0.503 eps=1.8210053077346027
MinPts=54
Clustering
Hierarchical Clustering 0.803 method=single
k=2
Clustering
fanny 0.819 k=2
membexp=1.3966666666666667
Clustering
k-Means 0.932 k=2
nstart=10
Clustering
DensityCut 0.501 alpha=0.20833333333333331
K=3
Clustering
clusterONE 0.698 s=3
d=0.9333333333333333
Clustering
Markov Clustering 0.497 I=1.117817817817818 Clustering
Transitivity Clustering 0.604 T=4.520613776958774 Clustering
MCODE 0.551 v=0.8
cutoff=4.552513269336507
haircut=T
fluff=T
Clustering