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=29
samples=20
Clustering
Self Organizing Maps 0.0 x=18
y=36
Clustering
Spectral Clustering 0.423 k=33 Clustering
clusterdp 0.0 k=19
dc=0.2237311883923943
Clustering
HDBSCAN 0.0 minPts=11
k=29
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=35
Clustering
c-Means 0.0 k=23
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=30 Clustering
DIANA 0.0 metric=euclidean
k=35
Clustering
DBSCAN 0.0 eps=0.08135679577905247
MinPts=38
Clustering
Hierarchical Clustering 0.0 method=complete
k=36
Clustering
fanny 0.007 k=16
membexp=1.1
Clustering
k-Means 0.0 k=35
nstart=10
Clustering
DensityCut 0.15 alpha=0.7657180059523809
K=2
Clustering
clusterONE 0.057 s=3
d=0.8
Clustering
Affinity Propagation 0.0 dampfact=0.7
preference=0.6101759683428936
maxits=2000
convits=500
Clustering
Markov Clustering 0.341 I=9.884184184184184 Clustering
Transitivity Clustering 0.0 T=0.5124500875272149 Clustering