Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » zahn_compound » Best Parameters
Navigation:
027Hints:

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=226
samples=20		 Clustering
Self Organizing Maps 0.0 x=385
y=239		 Clustering
Spectral Clustering 0.014 k=24 Clustering
clusterdp 0.072 k=24
dc=3.6781585066443236		 Clustering
HDBSCAN 0.0 minPts=13
k=79		 Clustering
AGNES 0.0 method=average
metric=euclidean
k=282		 Clustering
c-Means 0.0 k=378
m=1.5		 Clustering
k-Medoids (PAM) 0.0 k=273 Clustering
DIANA 0.0 metric=euclidean
k=281		 Clustering
DBSCAN 0.0 eps=7.356317013288647
MinPts=332		 Clustering
Hierarchical Clustering 0.0 method=single
k=330		 Clustering
fanny 0.0 k=102
membexp=1.1		 Clustering
k-Means 0.0 k=342
nstart=10		 Clustering
DensityCut 0.192 alpha=0.2033730158730159
K=8		 Clustering
clusterONE 0.753 s=93
d=0.8333333333333334		 Clustering
Affinity Propagation 0.06 dampfact=0.845
preference=27.586188799832428
maxits=5000
convits=200		 Clustering
Markov Clustering 0.753 I=1.4207207207207209 Clustering
Transitivity Clustering 0.0 T=35.640214558875925 Clustering
MCODE 0.043 v=0.1
cutoff=32.183886933137835
haircut=T
fluff=F		 Clustering