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=85
samples=20		 Clustering
Self Organizing Maps 0.0 x=240
y=240		 Clustering
Spectral Clustering 0.002 k=34 Clustering
clusterdp 0.0 k=8
dc=2.459745357190907		 Clustering
HDBSCAN 0.0 minPts=15
k=128		 Clustering
AGNES 0.0 method=average
metric=euclidean
k=71		 Clustering
c-Means 0.0 k=223
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=111 Clustering
DIANA 0.0 metric=euclidean
k=158		 Clustering
DBSCAN 0.0 eps=4.919490714381814
MinPts=16		 Clustering
Hierarchical Clustering 0.0 method=complete
k=189		 Clustering
fanny 0.0 k=59
membexp=2.0		 Clustering
k-Means 0.0 k=211
nstart=10		 Clustering
DensityCut 0.0 alpha=0.5753348214285714
K=12		 Clustering
clusterONE 1.0 s=104
d=0.03333333333333333		 Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=14.758472143145443
maxits=5000
convits=350		 Clustering
Markov Clustering 1.0 I=1.500900900900901 Clustering
Transitivity Clustering 0.0 T=13.812984438279267 Clustering
MCODE 0.009 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering