Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » veenman_r15 » 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=465
samples=20		 Clustering
Self Organizing Maps 0.0 x=600
y=540		 Clustering
Spectral Clustering 0.013 k=39 Clustering
clusterdp 0.003 k=17
dc=0.9295510122873538		 Clustering
HDBSCAN 0.0 minPts=58
k=457		 Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=563		 Clustering
c-Means 0.0 k=533
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=558 Clustering
DIANA 0.0 metric=euclidean
k=561		 Clustering
DBSCAN 0.0 eps=0.4647755061436769
MinPts=280		 Clustering
Hierarchical Clustering 0.0 method=average
k=452		 Clustering
fanny 0.0 k=268
membexp=2.0		 Clustering
k-Means 0.0 k=468
nstart=10		 Clustering
DensityCut 0.007 alpha=0.3309523809523809
K=24		 Clustering
clusterONE 0.935 s=440
d=0.8		 Clustering
Affinity Propagation 0.004 dampfact=0.99
preference=10.457448888232731
maxits=2000
convits=500		 Clustering
Markov Clustering 0.935 I=7.1580580580580575 Clustering
Transitivity Clustering 0.0 T=13.88743629468344 Clustering
MCODE 0.017 v=0.5
cutoff=12.781326418951116
haircut=F
fluff=F		 Clustering