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=143
k=200
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=197
Clustering
c-Means 0.0 k=122
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=198 Clustering
DIANA 0.0 metric=euclidean
k=200
Clustering
DBSCAN 0.0 eps=1.8210053077346027
MinPts=54
Clustering
Hierarchical Clustering 0.0 method=average
k=200
Clustering
fanny 0.0 k=8
membexp=8.813333333333333
Clustering
k-Means 0.0 k=198
nstart=10
Clustering
DensityCut 0.733 alpha=0.4583333333333333
K=3
Clustering
clusterONE 0.02 s=8
d=0.6
Clustering
Markov Clustering 1.0 I=6.480980980980981 Clustering
Transitivity Clustering 0.0 T=8.366781143645474 Clustering
MCODE 0.063 v=0.3
cutoff=4.552513269336507
haircut=F
fluff=F
Clustering