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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=150
samples=20		 Clustering
Self Organizing Maps 1.0 x=109
y=84		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=13
dc=1.3582306799958523		 Clustering
HDBSCAN 1.0 minPts=36
k=24		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=10		 Clustering
c-Means 1.0 k=37
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=207 Clustering
DIANA 1.0 metric=euclidean
k=45		 Clustering
DBSCAN 1.0 eps=0.6268756984596242
MinPts=191		 Clustering
Hierarchical Clustering 1.0 method=average
k=92		 Clustering
fanny 1.0 k=26
membexp=1.1		 Clustering
k-Means 1.0 k=125
nstart=10		 Clustering
DensityCut 1.0 alpha=0.025829081632653062
K=19		 Clustering
clusterONE 0.0 s=142
d=0.4666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=1.1753919346117954
maxits=2000
convits=425		 Clustering
Markov Clustering 0.0 I=2.16016016016016 Clustering
Transitivity Clustering 1.0 T=1.2361813072727323 Clustering
MCODE 1.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=F		 Clustering