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 0.548 metric=euclidean
k=11
samples=20
Clustering
Self Organizing Maps 0.42 x=2
y=224
Clustering
Spectral Clustering 0.736 k=6 Clustering
clusterdp 1.0 k=24
dc=1.4758472143145445
Clustering
HDBSCAN 0.822 minPts=2
k=12
Clustering
AGNES 0.822 method=weighted
metric=euclidean
k=10
Clustering
c-Means 0.611 k=3
m=1.5
Clustering
k-Medoids (PAM) 0.558 k=4 Clustering
DIANA 0.582 metric=euclidean
k=5
Clustering
DBSCAN 0.909 eps=12.298726785954536
MinPts=184
Clustering
Hierarchical Clustering 0.822 method=single
k=12
Clustering
fanny 0.607 k=4
membexp=5.0
Clustering
k-Means 0.54 k=4
nstart=10
Clustering
DensityCut 1.0 alpha=0.6666666666666666
K=12
Clustering
clusterONE 0.0 s=120
d=0.4
Clustering
Affinity Propagation 0.405 dampfact=0.99
preference=0.0
maxits=2000
convits=350
Clustering
Markov Clustering 0.0 I=7.746046046046047 Clustering
Transitivity Clustering 0.597 T=8.95258670545159 Clustering
MCODE 0.266 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T
Clustering