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=499
samples=20		 Clustering
Self Organizing Maps 0.0 x=600
y=540		 Clustering
Spectral Clustering 0.0 k=100 Clustering
clusterdp 0.0 k=19
dc=0.9295510122873538		 Clustering
HDBSCAN 0.0 minPts=28
k=140		 Clustering
AGNES 0.0 method=complete
metric=euclidean
k=592		 Clustering
c-Means 0.0 k=62
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=540 Clustering
DIANA 0.0 metric=euclidean
k=484		 Clustering
DBSCAN 0.0 eps=0.9295510122873538
MinPts=120		 Clustering
Hierarchical Clustering 0.0 method=complete
k=565		 Clustering
fanny 0.0 k=273
membexp=1.1		 Clustering
k-Means 0.0 k=388
nstart=10		 Clustering
DensityCut 0.0 alpha=0.38095237722709063
K=28		 Clustering
clusterONE 1.0 s=300
d=0.7		 Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=10.457448888232731
maxits=5000
convits=500		 Clustering
Markov Clustering 1.0 I=9.02002002002002 Clustering
Transitivity Clustering 0.0 T=13.88743629468344 Clustering
MCODE 0.001 v=0.9
cutoff=13.36229580163071
haircut=T
fluff=F		 Clustering