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=197
samples=20
Clustering
Self Organizing Maps 0.0 x=200
y=160
Clustering
Spectral Clustering 0.005 k=110 Clustering
clusterdp 0.043 k=3
dc=4.856014153958941
Clustering
HDBSCAN 0.0 minPts=29
k=200
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=200
Clustering
c-Means 0.0 k=3
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=195 Clustering
DIANA 0.0 metric=euclidean
k=199
Clustering
DBSCAN 0.0 eps=12.74703715414222
MinPts=20
Clustering
Hierarchical Clustering 0.0 method=complete
k=198
Clustering
fanny 0.0 k=54
membexp=6.44
Clustering
k-Means 0.0 k=198
nstart=10
Clustering
DensityCut 0.733 alpha=0.4583333333333333
K=3
Clustering
clusterONE 0.02 s=2
d=0.6333333333333333
Clustering
Markov Clustering 1.0 I=4.2092092092092095 Clustering
Transitivity Clustering 0.0 T=17.13458447718245 Clustering
MCODE 0.063 v=0.2
cutoff=4.552513269336507
haircut=T
fluff=T
Clustering