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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=108
samples=20		 Clustering
Self Organizing Maps 1.0 x=233
y=233		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=23
dc=0.47015677384471816		 Clustering
HDBSCAN 1.0 minPts=5
k=18		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=28		 Clustering
c-Means 1.0 k=3
m=5.0		 Clustering
k-Medoids (PAM) 1.0 k=231 Clustering
DIANA 1.0 metric=euclidean
k=203		 Clustering
DBSCAN 1.0 eps=0.20895856615320804
MinPts=34		 Clustering
Hierarchical Clustering 1.0 method=average
k=250		 Clustering
fanny 1.0 k=82
membexp=5.0		 Clustering
k-Means 1.0 k=123
nstart=10		 Clustering
DensityCut 1.0 alpha=0.044568452380952375
K=15		 Clustering
clusterONE 0.0 s=142
d=0.7666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=1.5671892461490604
maxits=2750
convits=200		 Clustering
Markov Clustering 0.0 I=2.997597597597598 Clustering
Transitivity Clustering 1.0 T=1.278537773384869 Clustering
MCODE 1.0 v=0.2
cutoff=1.1753919346117954
haircut=F
fluff=T		 Clustering