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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=652
samples=20		 Clustering
Self Organizing Maps 1.0 x=788
y=604		 Clustering
Spectral Clustering 1.0 k=118 Clustering
clusterdp 1.0 k=20
dc=2.587697389143054		 Clustering
HDBSCAN 1.0 minPts=132
k=578		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=118		 Clustering
c-Means 1.0 k=391
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=643 Clustering
DIANA 1.0 metric=euclidean
k=551		 Clustering
DBSCAN 1.0 eps=3.881546083714581
MinPts=630		 Clustering
Hierarchical Clustering 1.0 method=average
k=333		 Clustering
fanny 1.0 k=271
membexp=5.0		 Clustering
k-Means 1.0 k=415
nstart=10		 Clustering
DensityCut 1.0 alpha=1.52587890625E-5
K=10		 Clustering
clusterONE 0.0 s=394
d=0.43333333333333335		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=38.815460837145814
maxits=5000
convits=500		 Clustering
Markov Clustering 0.0 I=3.6657657657657663 Clustering
Transitivity Clustering 1.0 T=36.095658776484946 Clustering
MCODE 1.0 v=0.9
cutoff=35.58083910071699
haircut=T
fluff=T		 Clustering