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=171
samples=20
Clustering
Self Organizing Maps 0.0 x=2
y=50
Clustering
Spectral Clustering 0.0 k=17 Clustering
clusterdp 0.0 k=10
dc=1.3054020414582301
Clustering
HDBSCAN 0.0 minPts=8
k=88
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=213
Clustering
c-Means 0.0 k=244
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=220 Clustering
DIANA 0.0 metric=euclidean
k=68
Clustering
DBSCAN 0.0 eps=0.130540204145823
MinPts=67
Clustering
Hierarchical Clustering 0.0 method=average
k=121
Clustering
fanny 0.0 k=3
membexp=5.0
Clustering
k-Means 0.0 k=29
nstart=10
Clustering
DensityCut 0.0 alpha=0.9352678571428571
K=4
Clustering
clusterONE 1.0 s=1
d=0.23333333333333334
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=0.9790515310936726
maxits=5000
convits=200
Clustering
Markov Clustering 1.0 I=1.411811811811812 Clustering
Transitivity Clustering 0.0 T=2.8969732992121084 Clustering
MCODE 0.001 v=0.9
cutoff=3.589855614010133
haircut=T
fluff=T
Clustering