Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » bone_marrow_fixLabels » 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=31
samples=20		 Clustering
Self Organizing Maps 0.451 x=2
y=2		 Clustering
Spectral Clustering 0.032 k=11 Clustering
clusterdp 0.0 k=10
dc=0.18305279050286807		 Clustering
HDBSCAN 0.0 minPts=8
k=23		 Clustering
AGNES 0.067 method=average
metric=euclidean
k=11		 Clustering
c-Means 0.339 k=3
m=3.5		 Clustering
k-Medoids (PAM) 0.0 k=18 Clustering
DIANA 0.035 metric=euclidean
k=20		 Clustering
DBSCAN 0.639 eps=0.0
MinPts=10		 Clustering
Hierarchical Clustering 0.0 method=single
k=3		 Clustering
fanny 0.055 k=8
membexp=5.0		 Clustering
k-Means 0.047 k=3
nstart=10		 Clustering
DensityCut 0.199 alpha=0.4
K=2		 Clustering
clusterONE 0.639 s=1
d=0.03333333333333333		 Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=0.0
maxits=2000
convits=275		 Clustering
Markov Clustering 0.639 I=1.1534534534534537 Clustering
Transitivity Clustering 0.0 T=0.4519821987725138 Clustering
MCODE 0.639 v=0.0
cutoff=0.0
haircut=T
fluff=T		 Clustering