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Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:
Program Best quality Parameter set Clustering
CLARA 1.0 metric=euclidean
k=245
samples=20		 Clustering
Self Organizing Maps 1.0 x=188
y=63		 Clustering
Spectral Clustering 1.0 k=3 Clustering
clusterdp 1.0 k=21
dc=1.010258492774113		 Clustering
HDBSCAN 1.0 minPts=45
k=208		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=308		 Clustering
c-Means 1.0 k=40
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=85 Clustering
DIANA 1.0 metric=euclidean
k=116		 Clustering
DBSCAN 1.0 eps=25.25646231935282
MinPts=260		 Clustering
Hierarchical Clustering 1.0 method=average
k=125		 Clustering
fanny 1.0 k=99
membexp=2.0		 Clustering
k-Means 1.0 k=151
nstart=10		 Clustering
DensityCut 1.0 alpha=0.09920634920634921
K=13		 Clustering
clusterONE 0.0 s=260
d=0.5666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=15.153877391611694
maxits=5000
convits=500		 Clustering
Markov Clustering 0.0 I=6.783883883883885 Clustering
Transitivity Clustering 1.0 T=30.18640241171899 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=T		 Clustering