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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=19
samples=20		 Clustering
Self Organizing Maps 1.0 x=250
y=250		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=11
dc=0.9925531892277383		 Clustering
HDBSCAN 1.0 minPts=131
k=238		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=64		 Clustering
c-Means 1.0 k=5
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=14 Clustering
DIANA 1.0 metric=euclidean
k=78		 Clustering
DBSCAN 1.0 eps=0.05223964153830201
MinPts=84		 Clustering
Hierarchical Clustering 1.0 method=average
k=126		 Clustering
fanny 1.0 k=99
membexp=5.0		 Clustering
k-Means 1.0 k=196
nstart=10		 Clustering
DensityCut 1.0 alpha=0.05952380952380952
K=25		 Clustering
clusterONE 0.0 s=225
d=0.23333333333333334		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=0.7835946230745302
maxits=3500
convits=350		 Clustering
Markov Clustering 0.0 I=2.106706706706707 Clustering
Transitivity Clustering 1.0 T=1.4134509617420454 Clustering
MCODE 1.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=F		 Clustering