Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » fu_flame » 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=219
samples=20		 Clustering
Self Organizing Maps 0.0 x=73
y=208		 Clustering
Spectral Clustering 0.005 k=8 Clustering
clusterdp 0.0 k=17
dc=8.363134214449085		 Clustering
HDBSCAN 0.0 minPts=19
k=104		 Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=55		 Clustering
c-Means 0.0 k=206
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=221 Clustering
DIANA 0.0 metric=euclidean
k=169		 Clustering
DBSCAN 0.0 eps=4.919490714381814
MinPts=16		 Clustering
Hierarchical Clustering 0.0 method=single
k=28		 Clustering
fanny 0.0 k=46
membexp=2.0		 Clustering
k-Means 0.0 k=218
nstart=10		 Clustering
DensityCut 0.0 alpha=0.5526785714285714
K=8		 Clustering
clusterONE 0.464 s=48
d=0.43333333333333335		 Clustering
Affinity Propagation 0.014 dampfact=0.9175
preference=0.0
maxits=5000
convits=275		 Clustering
Markov Clustering 0.464 I=8.832932932932934 Clustering
Transitivity Clustering 0.0 T=13.872077419833406 Clustering
MCODE 0.175 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering