Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » brown » 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
Spectral Clustering 0.539 k=4 Clustering
clusterdp 0.482 k=6
dc=64.66124306862316		 Clustering
AGNES 0.1 method=flexible
metric=euclidean
k=43		 Clustering
c-Means 0.539 k=2
m=5.0		 Clustering
k-Medoids (PAM) 0.112 k=47 Clustering
DIANA 0.123 metric=euclidean
k=55		 Clustering
DBSCAN 0.405 eps=21.553747689541055
MinPts=24		 Clustering
Hierarchical Clustering 0.077 method=single
k=49		 Clustering
fanny 0.484 k=39
membexp=2.0		 Clustering
clusterONE 0.558 s=16
d=0.43333333333333335		 Clustering
Affinity Propagation 0.5 dampfact=0.7725
preference=242.47966150733686
maxits=4250
convits=200		 Clustering
Markov Clustering 0.49 I=1.1 Clustering
Transitivity Clustering 0.025 T=264.7292133640328 Clustering
MCODE 0.499 v=0
cutoff=242.47966150733683
haircut=F
fluff=F		 Clustering