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=18
y=36		 Clustering
Spectral Clustering 0.423 k=33 Clustering
clusterdp 0.0 k=2
dc=0.3050879841714468		 Clustering
HDBSCAN 0.0 minPts=6
k=38		 Clustering
AGNES 0.0 method=single
metric=euclidean
k=33		 Clustering
c-Means 0.0 k=3
m=1.01		 Clustering
k-Medoids (PAM) 0.0 k=33 Clustering
DIANA 0.0 metric=euclidean
k=35		 Clustering
DBSCAN 0.0 eps=0.06101759683428935
MinPts=30		 Clustering
Hierarchical Clustering 0.0 method=complete
k=37		 Clustering
fanny 0.007 k=18
membexp=1.1		 Clustering
k-Means 0.0 k=35
nstart=10		 Clustering
DensityCut 0.15 alpha=0.7436011904761904
K=2		 Clustering
clusterONE 0.057 s=5
d=0.8		 Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=0.6101759683428936
maxits=4250
convits=275		 Clustering
Markov Clustering 0.341 I=9.955455455455455 Clustering
Transitivity Clustering 0.0 T=0.5942955127103458 Clustering