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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=218
samples=20		 Clustering
Self Organizing Maps 1.0 x=250
y=250		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=12
dc=0.7835946230745302		 Clustering
HDBSCAN 1.0 minPts=18
k=18		 Clustering
AGNES 1.0 method=single
metric=euclidean
k=55		 Clustering
c-Means 1.0 k=37
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=10 Clustering
DIANA 1.0 metric=euclidean
k=63		 Clustering
DBSCAN 1.0 eps=0.2611982076915101
MinPts=17		 Clustering
Hierarchical Clustering 1.0 method=single
k=74		 Clustering
fanny 1.0 k=6
membexp=1.1		 Clustering
k-Means 1.0 k=173
nstart=10		 Clustering
DensityCut 1.0 alpha=0.047619047619047616
K=36		 Clustering
clusterONE 0.0 s=191
d=1.0		 Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=1.1753919346117954
maxits=2750
convits=425		 Clustering
Markov Clustering 0.0 I=2.2581581581581585 Clustering
Transitivity Clustering 1.0 T=1.4244322677711179 Clustering
MCODE 1.0 v=0.2
cutoff=1.3059910384575504
haircut=T
fluff=F		 Clustering