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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=190
samples=20		 Clustering
Self Organizing Maps 1.0 x=225
y=108		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=7
dc=1.2537513969192484		 Clustering
HDBSCAN 1.0 minPts=250
k=238		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=234		 Clustering
c-Means 1.0 k=37
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=229 Clustering
DIANA 1.0 metric=euclidean
k=45		 Clustering
DBSCAN 1.0 eps=1.5149496046107584
MinPts=183		 Clustering
Hierarchical Clustering 1.0 method=complete
k=84		 Clustering
fanny 1.0 k=49
membexp=5.0		 Clustering
k-Means 1.0 k=168
nstart=10		 Clustering
DensityCut 1.0 alpha=0.03968253968253968
K=25		 Clustering
clusterONE 0.0 s=175
d=0.23333333333333334		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=1.5671892461490604
maxits=2000
convits=350		 Clustering
Markov Clustering 0.0 I=2.65015015015015 Clustering
Transitivity Clustering 1.0 T=1.2424563392893453 Clustering
MCODE 1.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=F		 Clustering