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 0.841 metric=euclidean
k=1
samples=20
Clustering
Self Organizing Maps 0.841 x=2
y=1
Clustering
Spectral Clustering 0.838 k=4 Clustering
clusterdp 1.0 k=23
dc=1.9677962857527258
Clustering
HDBSCAN 0.956 minPts=2
k=12
Clustering
AGNES 0.956 method=complete
metric=euclidean
k=18
Clustering
c-Means 0.853 k=2
m=1.5
Clustering
k-Medoids (PAM) 0.848 k=2 Clustering
DIANA 0.852 metric=euclidean
k=2
Clustering
DBSCAN 0.985 eps=12.790675857392719
MinPts=184
Clustering
Hierarchical Clustering 0.956 method=single
k=12
Clustering
fanny 0.865 k=3
membexp=2.0
Clustering
k-Means 0.836 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.5982142857142857
K=9
Clustering
clusterONE 0.841 s=24
d=0.9666666666666667
Clustering
Affinity Propagation 0.841 dampfact=0.99
preference=0.0
maxits=5000
convits=200
Clustering
Markov Clustering 0.841 I=1.794894894894895 Clustering
Transitivity Clustering 0.841 T=0.029546490777067953 Clustering
MCODE 0.66 v=0.0
cutoff=13.52859946454999
haircut=T
fluff=T
Clustering