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 0.508 metric=euclidean
k=2
samples=20
Clustering
Self Organizing Maps 0.509 x=2
y=17
Clustering
Spectral Clustering 0.473 k=11 Clustering
clusterdp 0.506 k=18
dc=0.7832412248749381
Clustering
HDBSCAN 0.341 minPts=8
k=88
Clustering
AGNES 0.504 method=weighted
metric=euclidean
k=2
Clustering
c-Means 0.51 k=7
m=1.5
Clustering
k-Medoids (PAM) 0.508 k=3 Clustering
DIANA 0.508 metric=euclidean
k=2
Clustering
DBSCAN 0.473 eps=3.785665920228867
MinPts=225
Clustering
Hierarchical Clustering 0.502 method=average
k=4
Clustering
fanny NaN k=76
membexp=5.0
Clustering
k-Means 0.51 k=2
nstart=10
Clustering
DensityCut 0.478 alpha=0.7666666666666667
K=15
Clustering
clusterONE NaN s=150
d=0.1
Clustering
Affinity Propagation 0.411 dampfact=0.7725
preference=1.9581030621873452
maxits=2000
convits=350
Clustering
Markov Clustering NaN I=1.1356356356356356 Clustering
Transitivity Clustering 0.511 T=1.8816606003001515 Clustering
MCODE 0.475 v=0.7
cutoff=1.6317525518227878
haircut=F
fluff=F
Clustering