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=34
samples=20		 Clustering
Self Organizing Maps 0.0 x=34
y=10		 Clustering
Spectral Clustering 0.488 k=26 Clustering
clusterdp 0.0 k=22
dc=0.2033919894476312		 Clustering
HDBSCAN 0.0 minPts=2
k=32		 Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=32		 Clustering
c-Means 0.0 k=33
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=36 Clustering
DIANA 0.0 metric=euclidean
k=29		 Clustering
DBSCAN 0.0 eps=0.2033919894476312
MinPts=8		 Clustering
Hierarchical Clustering 0.0 method=single
k=37		 Clustering
fanny 0.065 k=16
membexp=1.1		 Clustering
k-Means 0.0 k=29
nstart=10		 Clustering
DensityCut 0.23 alpha=0.8595238095238095
K=2		 Clustering
clusterONE 0.18 s=3
d=0.7333333333333333		 Clustering
Affinity Propagation 0.057 dampfact=0.7
preference=0.45763197625717017
maxits=3500
convits=275		 Clustering
Markov Clustering 0.369 I=9.955455455455455 Clustering
Transitivity Clustering 0.0 T=0.48740783056819725 Clustering