Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » bone_marrow » 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=29
samples=20		 Clustering
Self Organizing Maps 0.0 x=3
y=28		 Clustering
Spectral Clustering 0.423 k=33 Clustering
clusterdp 0.0 k=3
dc=0.2847487852266836		 Clustering
HDBSCAN 0.0 minPts=16
k=38		 Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=28		 Clustering
c-Means 0.0 k=38
m=1.01		 Clustering
k-Medoids (PAM) 0.0 k=36 Clustering
DIANA 0.0 metric=euclidean
k=38		 Clustering
DBSCAN 0.0 eps=0.040678397889526235
MinPts=29		 Clustering
Hierarchical Clustering 0.0 method=average
k=33		 Clustering
fanny 0.007 k=17
membexp=1.1		 Clustering
k-Means 0.0 k=33
nstart=10		 Clustering
DensityCut 0.15 alpha=0.7771577380952381
K=2		 Clustering
clusterONE 0.057 s=5
d=0.8		 Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=0.6101759683428936
maxits=4250
convits=275		 Clustering
Markov Clustering 0.341 I=9.928728728728728 Clustering
Transitivity Clustering 0.0 T=0.5185579550781948 Clustering