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=196
samples=20
Clustering
Self Organizing Maps 0.051 x=200
y=160
Clustering
Spectral Clustering 0.068 k=4 Clustering
clusterdp 0.355 k=13
dc=8.498024769428147
Clustering
HDBSCAN 0.456 minPts=19
k=162
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=200
Clustering
c-Means 0.0 k=198
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=198 Clustering
DIANA 0.0 metric=euclidean
k=200
Clustering
DBSCAN 0.503 eps=18.21005307734603
MinPts=173
Clustering
Hierarchical Clustering 0.0 method=average
k=199
Clustering
fanny 0.05 k=8
membexp=9.110000000000001
Clustering
k-Means 0.0 k=198
nstart=10
Clustering
DensityCut 0.501 alpha=0.4333333333333333
K=3
Clustering
clusterONE 0.148 s=6
d=0.6666666666666666
Clustering
Markov Clustering 0.503 I=5.322822822822823 Clustering
Transitivity Clustering 0.0 T=7.564736763862464 Clustering
MCODE 0.389 v=0.5
cutoff=4.552513269336507
haircut=T
fluff=F
Clustering