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 0.251 metric=euclidean
k=37
samples=20
Clustering
Self Organizing Maps 0.568 x=28
y=38
Clustering
Spectral Clustering 0.665 k=26 Clustering
clusterdp 0.291 k=19
dc=0.0
Clustering
HDBSCAN 0.0 minPts=22
k=38
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=38
Clustering
c-Means 0.0 k=38
m=5.0
Clustering
k-Medoids (PAM) 0.193 k=36 Clustering
DIANA 0.0 metric=euclidean
k=38
Clustering
DBSCAN 0.0 eps=0.16271359155810494
MinPts=5
Clustering
Hierarchical Clustering 0.0 method=complete
k=38
Clustering
fanny 0.414 k=3
membexp=2.0
Clustering
k-Means 0.254 k=36
nstart=10
Clustering
DensityCut 0.623 alpha=0.7558035714285714
K=2
Clustering
clusterONE 0.472 s=2
d=0.0
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=0.6101759683428936
maxits=2000
convits=350
Clustering
Markov Clustering 0.623 I=9.786186186186185 Clustering
Transitivity Clustering 0.0 T=0.5032882862007451 Clustering