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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=74
samples=20		 Clustering
Self Organizing Maps 1.0 x=2
y=9		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=10
dc=1.3059910384575502		 Clustering
HDBSCAN 1.0 minPts=7
k=5		 Clustering
AGNES 1.0 method=complete
metric=euclidean
k=19		 Clustering
c-Means 1.0 k=3
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=83 Clustering
DIANA 1.0 metric=euclidean
k=7		 Clustering
DBSCAN 1.0 eps=0.10447928307660402
MinPts=50		 Clustering
Hierarchical Clustering 1.0 method=average
k=180		 Clustering
fanny 1.0 k=56
membexp=5.0		 Clustering
k-Means 1.0 k=153
nstart=10		 Clustering
DensityCut 1.0 alpha=0.6666666666666666
K=24		 Clustering
clusterONE 0.0 s=200
d=0.43333333333333335		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=1.5671892461490604
maxits=5000
convits=350		 Clustering
Markov Clustering 0.0 I=2.721421421421421 Clustering
Transitivity Clustering 1.0 T=1.248731371305958 Clustering
MCODE 1.0 v=0.6
cutoff=1.2406914865346728
haircut=F
fluff=T		 Clustering