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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=554
samples=20		 Clustering
Self Organizing Maps 1.0 x=600
y=60		 Clustering
Spectral Clustering 1.0 k=100 Clustering
clusterdp 1.0 k=22
dc=0.9295510122873538		 Clustering
HDBSCAN 1.0 minPts=86
k=200		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=585		 Clustering
c-Means 1.0 k=394
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=501 Clustering
DIANA 1.0 metric=euclidean
k=477		 Clustering
DBSCAN 1.0 eps=0.4647755061436769
MinPts=280		 Clustering
Hierarchical Clustering 1.0 method=complete
k=598		 Clustering
fanny 1.0 k=155
membexp=2.0		 Clustering
k-Means 1.0 k=538
nstart=10		 Clustering
DensityCut 1.0 alpha=0.40773809523809523
K=11		 Clustering
clusterONE 0.0 s=440
d=0.1		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=13.943265184310308
maxits=5000
convits=200		 Clustering
Markov Clustering 0.0 I=2.4986986986986985 Clustering
Transitivity Clustering 1.0 T=13.88743629468344 Clustering
MCODE 0.999 v=0.8
cutoff=13.36229580163071
haircut=T
fluff=T		 Clustering