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=weighted
metric=euclidean
k=195
Clustering
c-Means 0.0 k=198
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=198 Clustering
DIANA 0.0 metric=euclidean
k=200
Clustering
DBSCAN 0.503 eps=4.856014153958941
MinPts=34
Clustering
Hierarchical Clustering 0.0 method=complete
k=198
Clustering
fanny 0.05 k=8
membexp=9.110000000000001
Clustering
k-Means 0.0 k=199
nstart=10
Clustering
DensityCut 0.501 alpha=0.20833333333333331
K=3
Clustering
clusterONE 0.148 s=6
d=0.6666666666666666
Clustering
Markov Clustering 0.503 I=1.8572572572572574 Clustering
Transitivity Clustering 0.0 T=7.017888323101323 Clustering
MCODE 0.389 v=0.5
cutoff=4.552513269336507
haircut=T
fluff=T
Clustering