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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=43
samples=20		 Clustering
Self Organizing Maps 1.0 x=233
y=233		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=21
dc=0.05223964153830201		 Clustering
HDBSCAN 1.0 minPts=143
k=238		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=18		 Clustering
c-Means 1.0 k=11
m=5.0		 Clustering
k-Medoids (PAM) 1.0 k=234 Clustering
DIANA 1.0 metric=euclidean
k=40		 Clustering
DBSCAN 1.0 eps=1.5149496046107584
MinPts=183		 Clustering
Hierarchical Clustering 1.0 method=single
k=218		 Clustering
fanny 1.0 k=94
membexp=2.0		 Clustering
k-Means 1.0 k=93
nstart=10		 Clustering
DensityCut 1.0 alpha=0.17857142857142855
K=25		 Clustering
clusterONE 0.0 s=233
d=0.5333333333333333		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=1.1753919346117954
maxits=3500
convits=500		 Clustering
Markov Clustering 0.0 I=1.6434434434434437 Clustering
Transitivity Clustering 1.0 T=1.4291385417835776 Clustering
MCODE 1.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=F		 Clustering