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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=44
samples=20		 Clustering
Self Organizing Maps 1.0 x=175
y=225		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=16
dc=1.3059910384575502		 Clustering
HDBSCAN 1.0 minPts=84
k=250		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=79		 Clustering
c-Means 1.0 k=4
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=168 Clustering
DIANA 1.0 metric=euclidean
k=89		 Clustering
DBSCAN 1.0 eps=1.0970324723043423
MinPts=191		 Clustering
Hierarchical Clustering 1.0 method=single
k=81		 Clustering
fanny 1.0 k=74
membexp=1.1		 Clustering
k-Means 1.0 k=180
nstart=10		 Clustering
DensityCut 1.0 alpha=0.2777777777777778
K=5		 Clustering
clusterONE 0.0 s=167
d=0.43333333333333335		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=1.5671892461490604
maxits=2750
convits=500		 Clustering
Markov Clustering 0.0 I=1.411811811811812 Clustering
Transitivity Clustering 1.0 T=1.3130504494762398 Clustering
MCODE 1.0 v=0.8
cutoff=1.2406914865346728
haircut=T
fluff=T		 Clustering