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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=65
samples=20		 Clustering
Self Organizing Maps 1.0 x=250
y=250		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=16
dc=1.4104703215341545		 Clustering
HDBSCAN 1.0 minPts=4
k=10		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=64		 Clustering
c-Means 1.0 k=4
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=203 Clustering
DIANA 1.0 metric=euclidean
k=98		 Clustering
DBSCAN 1.0 eps=1.1492721138426443
MinPts=183		 Clustering
Hierarchical Clustering 1.0 method=complete
k=137		 Clustering
fanny 1.0 k=25
membexp=5.0		 Clustering
k-Means 1.0 k=123
nstart=10		 Clustering
DensityCut 1.0 alpha=0.03660714285714285
K=24		 Clustering
clusterONE 0.0 s=167
d=0.9		 Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=1.5671892461490604
maxits=4250
convits=500		 Clustering
Markov Clustering 0.0 I=2.071071071071071 Clustering
Transitivity Clustering 1.0 T=1.2518688873142645 Clustering
MCODE 1.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=F		 Clustering