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 1.0 metric=euclidean
k=161
samples=20		 Clustering
Self Organizing Maps 1.0 x=57
y=144		 Clustering
Spectral Clustering 0.998 k=34 Clustering
clusterdp 1.0 k=14
dc=2.459745357190907		 Clustering
HDBSCAN 1.0 minPts=1
k=183		 Clustering
AGNES 1.0 method=complete
metric=euclidean
k=69		 Clustering
c-Means 1.0 k=170
m=5.0		 Clustering
k-Medoids (PAM) 1.0 k=231 Clustering
DIANA 1.0 metric=euclidean
k=232		 Clustering
DBSCAN 1.0 eps=8.855083285887266
MinPts=176		 Clustering
Hierarchical Clustering 1.0 method=complete
k=25		 Clustering
fanny 1.0 k=118
membexp=5.0		 Clustering
k-Means 1.0 k=205
nstart=10		 Clustering
DensityCut 1.0 alpha=0.566220238095238
K=10		 Clustering
clusterONE 0.0 s=104
d=0.06666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=14.758472143145443
maxits=2000
convits=275		 Clustering
Markov Clustering 0.0 I=2.0265265265265264 Clustering
Transitivity Clustering 1.0 T=14.211862063769685 Clustering
MCODE 0.991 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering