Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » astral_40_seqsim_beh » 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 0.0 k=1044 Clustering
clusterdp 0.0 k=733
dc=30.85305866782294		 Clustering
AGNES 0.0 method=single
metric=euclidean
k=677		 Clustering
c-Means 0.0 k=252
m=5.0		 Clustering
k-Medoids (PAM) 0.0 k=958 Clustering
DIANA 0.0 metric=euclidean
k=707		 Clustering
DBSCAN 0.0 eps=92.5591760034688
MinPts=628		 Clustering
Hierarchical Clustering 0.0 method=average
k=788		 Clustering
fanny 0.0 k=401
membexp=2.0		 Clustering
clusterONE 0.012 s=1
d=0.36666666666666664		 Clustering
Affinity Propagation 0.0 dampfact=0.7
preference=86.774227503252
maxits=4250
convits=275		 Clustering
Markov Clustering 0.001 I=10.0 Clustering
Transitivity Clustering 0.0 T=97.51604879244337 Clustering
MCODE 0.32 v=0.8
cutoff=4.820790416847334
haircut=F
fluff=T		 Clustering