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 1.0 metric=euclidean
k=30
samples=20
Clustering
Self Organizing Maps 1.0 x=38
y=38
Clustering
Spectral Clustering 0.577 k=33 Clustering
clusterdp 1.0 k=3
dc=0.2847487852266836
Clustering
HDBSCAN 1.0 minPts=27
k=34
Clustering
AGNES 1.0 method=complete
metric=euclidean
k=26
Clustering
c-Means 1.0 k=32
m=1.5
Clustering
k-Medoids (PAM) 1.0 k=35 Clustering
DIANA 1.0 metric=euclidean
k=33
Clustering
DBSCAN 1.0 eps=0.16271359155810494
MinPts=5
Clustering
Hierarchical Clustering 1.0 method=single
k=31
Clustering
fanny 0.993 k=18
membexp=1.1
Clustering
k-Means 1.0 k=32
nstart=10
Clustering
DensityCut 0.85 alpha=0.7558035714285714
K=2
Clustering
clusterONE 0.943 s=5
d=0.8
Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=0.6101759683428936
maxits=2000
convits=350
Clustering
Markov Clustering 0.659 I=9.93763763763764 Clustering
Transitivity Clustering 1.0 T=0.4922941246089812 Clustering