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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=162
samples=20		 Clustering
Self Organizing Maps 1.0 x=250
y=250		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=17
dc=1.5149496046107584		 Clustering
HDBSCAN 1.0 minPts=59
k=59		 Clustering
AGNES 1.0 method=single
metric=euclidean
k=20		 Clustering
c-Means 1.0 k=4
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=49 Clustering
DIANA 1.0 metric=euclidean
k=110		 Clustering
DBSCAN 1.0 eps=0.7835946230745302
MinPts=216		 Clustering
Hierarchical Clustering 1.0 method=complete
k=121		 Clustering
fanny 1.0 k=64
membexp=2.0		 Clustering
k-Means 1.0 k=159
nstart=10		 Clustering
DensityCut 1.0 alpha=0.06101190476190475
K=24		 Clustering
clusterONE 0.0 s=216
d=0.8		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=0.7835946230745302
maxits=3500
convits=425		 Clustering
Markov Clustering 0.0 I=1.1534534534534537 Clustering
Transitivity Clustering 1.0 T=1.0526366207868063 Clustering
MCODE 1.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=F		 Clustering