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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=179
samples=20		 Clustering
Self Organizing Maps 1.0 x=233
y=233		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=7
dc=0.9403135476894363		 Clustering
HDBSCAN 1.0 minPts=202
k=250		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=17		 Clustering
c-Means 1.0 k=37
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=219 Clustering
DIANA 1.0 metric=euclidean
k=93		 Clustering
DBSCAN 1.0 eps=1.4104703215341545
MinPts=208		 Clustering
Hierarchical Clustering 1.0 method=average
k=151		 Clustering
fanny 1.0 k=61
membexp=2.0		 Clustering
k-Means 1.0 k=11
nstart=10		 Clustering
DensityCut 1.0 alpha=0.5714285714285714
K=24		 Clustering
clusterONE 0.0 s=225
d=0.03333333333333333		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=1.5671892461490604
maxits=4250
convits=425		 Clustering
Markov Clustering 0.0 I=2.249249249249249 Clustering
Transitivity Clustering 1.0 T=1.1797060191232165 Clustering
MCODE 1.0 v=0.1
cutoff=1.1753919346117954
haircut=T
fluff=T		 Clustering