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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=553
samples=20		 Clustering
Self Organizing Maps 1.0 x=101
y=40		 Clustering
Spectral Clustering 1.0 k=100 Clustering
clusterdp 1.0 k=24
dc=0.9295510122873538		 Clustering
HDBSCAN 1.0 minPts=24
k=201		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=505		 Clustering
c-Means 1.0 k=56
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=516 Clustering
DIANA 1.0 metric=euclidean
k=555		 Clustering
DBSCAN 1.0 eps=0.4647755061436769
MinPts=280		 Clustering
Hierarchical Clustering 1.0 method=average
k=529		 Clustering
fanny 1.0 k=275
membexp=1.1		 Clustering
k-Means 1.0 k=497
nstart=10		 Clustering
DensityCut 1.0 alpha=0.2642857142857143
K=24		 Clustering
clusterONE 0.0 s=600
d=0.8		 Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=13.943265184310308
maxits=2750
convits=275		 Clustering
Markov Clustering 0.0 I=7.656956956956958 Clustering
Transitivity Clustering 1.0 T=13.915350739496873 Clustering
MCODE 0.999 v=0.8
cutoff=13.36229580163071
haircut=T
fluff=T		 Clustering