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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=351
samples=20		 Clustering
Self Organizing Maps 1.0 x=399
y=359		 Clustering
Spectral Clustering 0.999 k=24 Clustering
clusterdp 0.991 k=3
dc=4.904211342192431		 Clustering
HDBSCAN 1.0 minPts=11
k=92		 Clustering
AGNES 1.0 method=ward
metric=euclidean
k=214		 Clustering
c-Means 1.0 k=79
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=142 Clustering
DIANA 1.0 metric=euclidean
k=140		 Clustering
DBSCAN 1.0 eps=7.356317013288647
MinPts=332		 Clustering
Hierarchical Clustering 1.0 method=single
k=351		 Clustering
fanny 1.0 k=186
membexp=2.0		 Clustering
k-Means 1.0 k=211
nstart=10		 Clustering
DensityCut 0.935 alpha=0.12152777777777776
K=3		 Clustering
clusterONE 0.0 s=14
d=0.8		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=36.781585066443235
maxits=3500
convits=425		 Clustering
Markov Clustering 0.0 I=6.240440440440441 Clustering
Transitivity Clustering 1.0 T=36.781585066443235 Clustering
MCODE 0.996 v=0.1
cutoff=32.183886933137835
haircut=T
fluff=T		 Clustering