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 0.892 metric=euclidean
k=7
samples=20
Clustering
Self Organizing Maps NaN x=2
y=2
Clustering
Spectral Clustering 0.959 k=2 Clustering
clusterdp 0.963 k=3
dc=0.06101759683428935
Clustering
HDBSCAN 0.809 minPts=8
k=23
Clustering
AGNES 0.923 method=complete
metric=euclidean
k=3
Clustering
c-Means NaN k=3
m=3.5
Clustering
k-Medoids (PAM) 0.929 k=5 Clustering
DIANA NaN metric=euclidean
k=10
Clustering
DBSCAN 0.639 eps=0.0
MinPts=3
Clustering
Hierarchical Clustering NaN method=complete
k=2
Clustering
fanny 0.959 k=2
membexp=2.0
Clustering
k-Means 0.959 k=8
nstart=10
Clustering
DensityCut 0.885 alpha=0.43333333333333335
K=2
Clustering
clusterONE 0.361 s=1
d=0.0
Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 0.361 I=1.1623623623623625 Clustering
Transitivity Clustering 0.974 T=0.26324909144723435 Clustering
MCODE 0.361 v=0.0
cutoff=0.0
haircut=T
fluff=T
Clustering