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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=120
samples=20		 Clustering
Self Organizing Maps 1.0 x=10
y=1		 Clustering
Spectral Clustering 1.0 k=17 Clustering
clusterdp 1.0 k=5
dc=0.6527010207291151		 Clustering
HDBSCAN 1.0 minPts=72
k=250		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=243		 Clustering
c-Means 1.0 k=64
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=242 Clustering
DIANA 1.0 metric=euclidean
k=54		 Clustering
DBSCAN 1.0 eps=2.741344287062283
MinPts=191		 Clustering
Hierarchical Clustering 1.0 method=average
k=191		 Clustering
fanny 1.0 k=65
membexp=5.0		 Clustering
k-Means 1.0 k=95
nstart=10		 Clustering
DensityCut 1.0 alpha=0.9375
K=3		 Clustering
clusterONE 0.0 s=208
d=0.8333333333333334		 Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=0.9790515310936726
maxits=2000
convits=425		 Clustering
Markov Clustering 0.0 I=2.890690690690691 Clustering
Transitivity Clustering 1.0 T=2.8420915317033537 Clustering
MCODE 0.999 v=0.6
cutoff=3.589855614010133
haircut=T
fluff=T		 Clustering