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 0.331 metric=euclidean
k=1
samples=20
Clustering
Self Organizing Maps 0.247 x=2
y=1
Clustering
Spectral Clustering 0.854 k=3 Clustering
clusterdp 1.0 k=3
dc=4.041033971096452
Clustering
HDBSCAN 0.813 minPts=5
k=34
Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=3
Clustering
c-Means 0.247 k=7
m=2.25
Clustering
k-Medoids (PAM) 0.248 k=13 Clustering
DIANA 0.331 metric=euclidean
k=4
Clustering
DBSCAN 1.0 eps=14.14361889883758
MinPts=280
Clustering
Hierarchical Clustering 1.0 method=complete
k=3
Clustering
fanny 0.331 k=8
membexp=2.0
Clustering
k-Means 0.247 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.2777777777777778
K=7
Clustering
clusterONE 0.331 s=1
d=0.0
Clustering
Affinity Propagation 0.331 dampfact=0.9175
preference=7.576938695805847
maxits=3500
convits=200
Clustering
Markov Clustering 0.331 I=1.1712712712712714 Clustering
Transitivity Clustering 0.331 T=0.06067618575219898 Clustering
MCODE 0.258 v=0.4
cutoff=17.679523623546974
haircut=T
fluff=T
Clustering