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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=98
samples=20		 Clustering
Self Organizing Maps 1.0 x=233
y=233		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=18
dc=1.0970324723043423		 Clustering
HDBSCAN 1.0 minPts=25
k=5		 Clustering
AGNES 1.0 method=single
metric=euclidean
k=137		 Clustering
c-Means 1.0 k=4
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=103 Clustering
DIANA 1.0 metric=euclidean
k=78		 Clustering
DBSCAN 1.0 eps=0.20895856615320804
MinPts=34		 Clustering
Hierarchical Clustering 1.0 method=average
k=145		 Clustering
fanny 1.0 k=107
membexp=1.1		 Clustering
k-Means 1.0 k=148
nstart=10		 Clustering
DensityCut 1.0 alpha=0.0384672619047619
K=8		 Clustering
clusterONE 0.0 s=183
d=0.9333333333333333		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=1.1753919346117954
maxits=3500
convits=275		 Clustering
Markov Clustering 0.0 I=3.0065065065065064 Clustering
Transitivity Clustering 1.0 T=1.2503001293101113 Clustering
MCODE 1.0 v=0.2
cutoff=1.3059910384575504
haircut=T
fluff=F		 Clustering