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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=87
samples=20		 Clustering
Self Organizing Maps 1.0 x=250
y=250		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=9
dc=1.4627099630724563		 Clustering
HDBSCAN 1.0 minPts=3
k=6		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=14		 Clustering
c-Means 1.0 k=37
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=20 Clustering
DIANA 1.0 metric=euclidean
k=7		 Clustering
DBSCAN 1.0 eps=0.2611982076915101
MinPts=17		 Clustering
Hierarchical Clustering 1.0 method=average
k=83		 Clustering
fanny 1.0 k=84
membexp=5.0		 Clustering
k-Means 1.0 k=26
nstart=10		 Clustering
DensityCut 1.0 alpha=0.0384672619047619
K=15		 Clustering
clusterONE 0.0 s=167
d=0.5666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=1.1753919346117954
maxits=5000
convits=200		 Clustering
Markov Clustering 0.0 I=8.61021021021021 Clustering
Transitivity Clustering 1.0 T=1.314619207480393 Clustering
MCODE 1.0 v=0.1
cutoff=1.1753919346117954
haircut=F
fluff=T		 Clustering