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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=54
samples=20		 Clustering
Self Organizing Maps 1.0 x=188
y=11		 Clustering
Spectral Clustering 1.0 k=86 Clustering
clusterdp 1.0 k=9
dc=19.194911362708144		 Clustering
HDBSCAN 1.0 minPts=1
k=237		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=293		 Clustering
c-Means 1.0 k=23
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=61 Clustering
DIANA 1.0 metric=euclidean
k=209		 Clustering
DBSCAN 1.0 eps=2.020516985548226
MinPts=1		 Clustering
Hierarchical Clustering 1.0 method=average
k=130		 Clustering
fanny 1.0 k=136
membexp=1.1		 Clustering
k-Means 1.0 k=151
nstart=10		 Clustering
DensityCut 1.0 alpha=0.01984126984126984
K=7		 Clustering
clusterONE 0.0 s=156
d=0.8333333333333334		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=22.73081608741754
maxits=4250
convits=500		 Clustering
Markov Clustering 0.0 I=1.4207207207207209 Clustering
Transitivity Clustering 1.0 T=30.00437385446239 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=T
fluff=T		 Clustering