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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=89
samples=20		 Clustering
Self Organizing Maps 1.0 x=250
y=250		 Clustering
Spectral Clustering 1.0 k=8 Clustering
clusterdp 1.0 k=9
dc=2.208		 Clustering
HDBSCAN 1.0 minPts=60
k=250		 Clustering
AGNES 1.0 method=complete
metric=euclidean
k=237		 Clustering
c-Means 1.0 k=57
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=219 Clustering
DIANA 1.0 metric=euclidean
k=122		 Clustering
DBSCAN 1.0 eps=3.0912
MinPts=175		 Clustering
Hierarchical Clustering 1.0 method=average
k=131		 Clustering
fanny 1.0 k=120
membexp=2.0		 Clustering
k-Means 1.0 k=155
nstart=10		 Clustering
DensityCut 1.0 alpha=0.03571196964808871
K=4		 Clustering
clusterONE 0.0 s=250
d=0.2		 Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=3.3120000000000003
maxits=3500
convits=425		 Clustering
Markov Clustering 0.5 I=9.688188188188189 Clustering
Transitivity Clustering 1.0 T=3.162810810810811 Clustering
MCODE 0.999 v=0.6
cutoff=3.036
haircut=T
fluff=T		 Clustering