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 0.477 metric=euclidean
k=37
samples=20
Clustering
Self Organizing Maps 0.462 x=105
y=52
Clustering
Spectral Clustering 0.912 k=3 Clustering
clusterdp 1.0 k=3
dc=4.041033971096452
Clustering
HDBSCAN 0.798 minPts=5
k=34
Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=3
Clustering
c-Means 0.489 k=27
m=1.01
Clustering
k-Medoids (PAM) 0.492 k=36 Clustering
DIANA 0.476 metric=euclidean
k=37
Clustering
DBSCAN 1.0 eps=14.14361889883758
MinPts=280
Clustering
Hierarchical Clustering 1.0 method=complete
k=3
Clustering
fanny 0.503 k=26
membexp=5.0
Clustering
k-Means 0.482 k=33
nstart=10
Clustering
DensityCut 1.0 alpha=0.0930059523809524
K=2
Clustering
clusterONE 0.0 s=115
d=0.5333333333333333
Clustering
Affinity Propagation 0.493 dampfact=0.7
preference=7.576938695805847
maxits=5000
convits=425
Clustering
Markov Clustering 0.0 I=3.4252252252252253 Clustering
Transitivity Clustering 0.536 T=25.423321830171368 Clustering
MCODE 0.468 v=0.5
cutoff=26.519285435320466
haircut=T
fluff=F
Clustering