Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » ppi_mips » 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 0.535 k=83 Clustering
clusterdp 0.311 k=949
dc=0.43333333333333335		 Clustering
AGNES 0.33 method=weighted
metric=euclidean
k=957		 Clustering
c-Means 0.306 k=695
m=2.25		 Clustering
k-Medoids (PAM) 0.822 k=130 Clustering
DIANA 0.334 metric=euclidean
k=978		 Clustering
DBSCAN 0.89 eps=0.13333333333333333
MinPts=729		 Clustering
Hierarchical Clustering 0.88 method=average
k=153		 Clustering
fanny 0.888 k=528
membexp=1.1		 Clustering
clusterONE 0.87 s=1
d=0.26666666666666666		 Clustering
Affinity Propagation 0.17 dampfact=0.7
preference=0.25
maxits=4250
convits=200		 Clustering
Markov Clustering 0.821 I=3.5855855855855854 Clustering
Transitivity Clustering 0.881 T=0.5425425425425425 Clustering