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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=4
samples=20		 Clustering
Self Organizing Maps 1.0 x=250
y=250		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=2
dc=1.5149496046107584		 Clustering
HDBSCAN 1.0 minPts=84
k=238		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=4		 Clustering
c-Means 1.0 k=42
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=242 Clustering
DIANA 1.0 metric=euclidean
k=40		 Clustering
DBSCAN 1.0 eps=0.9925531892277383
MinPts=225		 Clustering
Hierarchical Clustering 1.0 method=average
k=84		 Clustering
fanny 1.0 k=48
membexp=2.0		 Clustering
k-Means 1.0 k=42
nstart=10		 Clustering
DensityCut 1.0 alpha=0.06287202380952381
K=9		 Clustering
clusterONE 0.0 s=175
d=0.5666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=1.5671892461490604
maxits=4250
convits=200		 Clustering
Markov Clustering 0.0 I=8.77947947947948 Clustering
Transitivity Clustering 1.0 T=1.124799488977854 Clustering
MCODE 1.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=F		 Clustering