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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=34
samples=20		 Clustering
Self Organizing Maps 1.0 x=312
y=301		 Clustering
Spectral Clustering 1.0 k=52 Clustering
clusterdp 1.0 k=4
dc=18.184652869934034		 Clustering
HDBSCAN 1.0 minPts=223
k=312		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=7		 Clustering
c-Means 1.0 k=305
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=249 Clustering
DIANA 1.0 metric=euclidean
k=294		 Clustering
DBSCAN 1.0 eps=29.297496290449274
MinPts=260		 Clustering
Hierarchical Clustering 1.0 method=complete
k=264		 Clustering
fanny 1.0 k=103
membexp=5.0		 Clustering
k-Means 1.0 k=246
nstart=10		 Clustering
DensityCut 1.0 alpha=0.049479166666666664
K=10		 Clustering
clusterONE 0.0 s=83
d=0.8		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=30.307754783223388
maxits=2000
convits=350		 Clustering
Markov Clustering 0.0 I=3.2470470470470474 Clustering
Transitivity Clustering 1.0 T=27.21326930986124 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=T
fluff=T		 Clustering