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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=23
samples=20		 Clustering
Self Organizing Maps 1.0 x=788
y=604		 Clustering
Spectral Clustering 1.0 k=118 Clustering
clusterdp 1.0 k=23
dc=2.587697389143054		 Clustering
HDBSCAN 1.0 minPts=8
k=139		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=413		 Clustering
c-Means 1.0 k=134
m=5.0		 Clustering
k-Medoids (PAM) 1.0 k=719 Clustering
DIANA 1.0 metric=euclidean
k=415		 Clustering
DBSCAN 1.0 eps=6.469243472857636
MinPts=683		 Clustering
Hierarchical Clustering 1.0 method=average
k=612		 Clustering
fanny 1.0 k=262
membexp=2.0		 Clustering
k-Means 1.0 k=390
nstart=10		 Clustering
DensityCut 1.0 alpha=1.52587890625E-5
K=10		 Clustering
clusterONE 0.0 s=342
d=0.9		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=29.11159562785936
maxits=5000
convits=425		 Clustering
Markov Clustering 0.0 I=2.6768768768768765 Clustering
Transitivity Clustering 1.0 T=34.81346637645911 Clustering
MCODE 1.0 v=0.8
cutoff=35.58083910071699
haircut=T
fluff=T		 Clustering