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=197
samples=20
Clustering
Self Organizing Maps 1.0 x=200
y=160
Clustering
Spectral Clustering 0.995 k=110 Clustering
clusterdp 0.957 k=3
dc=4.856014153958941
Clustering
HDBSCAN 1.0 minPts=171
k=200
Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=197
Clustering
c-Means 1.0 k=132
m=2.25
Clustering
k-Medoids (PAM) 1.0 k=198 Clustering
DIANA 1.0 metric=euclidean
k=199
Clustering
DBSCAN 1.0 eps=10.926031846407618
MinPts=40
Clustering
Hierarchical Clustering 1.0 method=complete
k=198
Clustering
fanny 1.0 k=15
membexp=7.033333333333333
Clustering
k-Means 1.0 k=198
nstart=10
Clustering
DensityCut 0.267 alpha=0.4583333333333333
K=3
Clustering
clusterONE 0.98 s=8
d=0.6
Clustering
Markov Clustering 0.0 I=7.995495495495495 Clustering
Transitivity Clustering 1.0 T=9.041227553917548 Clustering
MCODE 0.937 v=0.2
cutoff=4.552513269336507
haircut=F
fluff=T
Clustering