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=174
samples=20		 Clustering
Self Organizing Maps 0.0 x=73
y=208		 Clustering
Spectral Clustering 0.002 k=34 Clustering
clusterdp 0.0 k=20
dc=10.330930500201811		 Clustering
HDBSCAN 0.0 minPts=2
k=12		 Clustering
AGNES 0.0 method=average
metric=euclidean
k=135		 Clustering
c-Means 0.0 k=158
m=5.0		 Clustering
k-Medoids (PAM) 0.0 k=231 Clustering
DIANA 0.0 metric=euclidean
k=228		 Clustering
DBSCAN 0.0 eps=5.411439785819995
MinPts=8		 Clustering
Hierarchical Clustering 0.0 method=average
k=32		 Clustering
fanny 0.0 k=75
membexp=1.1		 Clustering
k-Means 0.0 k=104
nstart=10		 Clustering
DensityCut 0.0 alpha=0.5714285714285714
K=12		 Clustering
clusterONE 1.0 s=192
d=0.6		 Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=14.758472143145443
maxits=3500
convits=425		 Clustering
Markov Clustering 1.0 I=9.57237237237237 Clustering
Transitivity Clustering 0.0 T=13.812984438279267 Clustering
MCODE 0.009 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering