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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=39
samples=20		 Clustering
Self Organizing Maps 1.0 x=2
y=208		 Clustering
Spectral Clustering 1.0 k=41 Clustering
clusterdp 1.0 k=20
dc=7.07180944941879		 Clustering
HDBSCAN 1.0 minPts=37
k=135		 Clustering
AGNES 1.0 method=single
metric=euclidean
k=137		 Clustering
c-Means 1.0 k=296
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=288 Clustering
DIANA 1.0 metric=euclidean
k=112		 Clustering
DBSCAN 1.0 eps=0.0
MinPts=11		 Clustering
Hierarchical Clustering 1.0 method=complete
k=103		 Clustering
fanny 1.0 k=95
membexp=1.1		 Clustering
k-Means 1.0 k=151
nstart=10		 Clustering
DensityCut 1.0 alpha=0.05617559523809523
K=8		 Clustering
clusterONE 0.0 s=260
d=0.6		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=22.73081608741754
maxits=2750
convits=350		 Clustering
Markov Clustering 0.0 I=6.222622622622622 Clustering
Transitivity Clustering 1.0 T=30.00437385446239 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=T		 Clustering