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 0.277 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.28 x=2
y=2
Clustering
Spectral Clustering 0.209 k=26 Clustering
clusterdp 0.357 k=5
dc=0.020339198944763118
Clustering
HDBSCAN 0.136 minPts=3
k=5
Clustering
AGNES 0.338 method=single
metric=euclidean
k=3
Clustering
c-Means 0.352 k=3
m=5.0
Clustering
k-Medoids (PAM) 0.366 k=3 Clustering
DIANA 0.312 metric=euclidean
k=7
Clustering
DBSCAN 0.36 eps=0.4881407746743148
MinPts=7
Clustering
Hierarchical Clustering 0.357 method=average
k=4
Clustering
fanny 0.352 k=3
membexp=1.1
Clustering
k-Means 0.352 k=3
nstart=10
Clustering
DensityCut 0.292 alpha=0.7558035714285714
K=2
Clustering
clusterONE 0.334 s=13
d=0.7333333333333333
Clustering
Affinity Propagation 0.371 dampfact=0.7
preference=0.0
maxits=2750
convits=425
Clustering
Markov Clustering 0.304 I=9.93763763763764 Clustering
Transitivity Clustering 0.36 T=0.289512921916448 Clustering