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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=458
samples=20		 Clustering
Self Organizing Maps 1.0 x=600
y=600		 Clustering
Spectral Clustering 1.0 k=100 Clustering
clusterdp 1.0 k=19
dc=0.9295510122873538		 Clustering
HDBSCAN 1.0 minPts=24
k=321		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=512		 Clustering
c-Means 1.0 k=128
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=472 Clustering
DIANA 1.0 metric=euclidean
k=573		 Clustering
DBSCAN 1.0 eps=0.9295510122873538
MinPts=120		 Clustering
Hierarchical Clustering 1.0 method=complete
k=526		 Clustering
fanny 1.0 k=290
membexp=5.0		 Clustering
k-Means 1.0 k=468
nstart=10		 Clustering
DensityCut 1.0 alpha=0.530952380952381
K=24		 Clustering
clusterONE 0.0 s=380
d=0.1		 Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=13.943265184310308
maxits=5000
convits=500		 Clustering
Markov Clustering 0.0 I=9.011111111111111 Clustering
Transitivity Clustering 1.0 T=13.943265184310308 Clustering
MCODE 0.999 v=0.8
cutoff=13.36229580163071
haircut=T
fluff=T		 Clustering