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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=199
samples=20		 Clustering
Self Organizing Maps 1.0 x=233
y=233		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=19
dc=0.05223964153830201		 Clustering
HDBSCAN 1.0 minPts=250
k=250		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=16		 Clustering
c-Means 1.0 k=6
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=94 Clustering
DIANA 1.0 metric=euclidean
k=7		 Clustering
DBSCAN 1.0 eps=1.3059910384575502
MinPts=225		 Clustering
Hierarchical Clustering 1.0 method=complete
k=135		 Clustering
fanny 1.0 k=16
membexp=5.0		 Clustering
k-Means 1.0 k=173
nstart=10		 Clustering
DensityCut 1.0 alpha=0.15873015873015872
K=25		 Clustering
clusterONE 0.0 s=216
d=0.5		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=1.1753919346117954
maxits=4250
convits=200		 Clustering
Markov Clustering 0.0 I=2.1334334334334337 Clustering
Transitivity Clustering 1.0 T=1.0620491688117257 Clustering
MCODE 1.0 v=0.2
cutoff=1.3059910384575504
haircut=T
fluff=F		 Clustering