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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=3
samples=20		 Clustering
Self Organizing Maps 1.0 x=2
y=9		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=13
dc=0.47015677384471816		 Clustering
HDBSCAN 1.0 minPts=20
k=64		 Clustering
AGNES 1.0 method=single
metric=euclidean
k=149		 Clustering
c-Means 1.0 k=37
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=172 Clustering
DIANA 1.0 metric=euclidean
k=52		 Clustering
DBSCAN 1.0 eps=0.8358342646128322
MinPts=241		 Clustering
Hierarchical Clustering 1.0 method=average
k=88		 Clustering
fanny 1.0 k=21
membexp=5.0		 Clustering
k-Means 1.0 k=217
nstart=10		 Clustering
DensityCut 1.0 alpha=0.05197704081632653
K=16		 Clustering
clusterONE 0.0 s=250
d=0.13333333333333333		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=1.1753919346117954
maxits=5000
convits=275		 Clustering
Markov Clustering 0.0 I=1.981981981981982 Clustering
Transitivity Clustering 1.0 T=1.3459943675634571 Clustering
MCODE 1.0 v=0.2
cutoff=1.3059910384575504
haircut=T
fluff=F		 Clustering