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=545
samples=20		 Clustering
Self Organizing Maps 0.0 x=600
y=540		 Clustering
Spectral Clustering 0.0 k=100 Clustering
clusterdp 0.0 k=22
dc=0.9295510122873538		 Clustering
HDBSCAN 0.0 minPts=28
k=140		 Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=548		 Clustering
c-Means 0.0 k=255
m=1.01		 Clustering
k-Medoids (PAM) 0.0 k=497 Clustering
DIANA 0.0 metric=euclidean
k=494		 Clustering
DBSCAN 0.0 eps=0.4647755061436769
MinPts=280		 Clustering
Hierarchical Clustering 0.0 method=single
k=515		 Clustering
fanny 0.0 k=185
membexp=1.1		 Clustering
k-Means 0.0 k=408
nstart=10		 Clustering
DensityCut 0.0 alpha=0.6190476190476191
K=29		 Clustering
clusterONE 1.0 s=600
d=0.0		 Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=10.457448888232731
maxits=5000
convits=500		 Clustering
Markov Clustering 1.0 I=1.3227227227227227 Clustering
Transitivity Clustering 0.0 T=13.88743629468344 Clustering
MCODE 0.001 v=0.9
cutoff=13.36229580163071
haircut=F
fluff=T		 Clustering