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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=157
samples=20		 Clustering
Self Organizing Maps 1.0 x=150
y=108		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=20
dc=0.5746360569213221		 Clustering
HDBSCAN 1.0 minPts=15
k=59		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=64		 Clustering
c-Means 1.0 k=187
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=122 Clustering
DIANA 1.0 metric=euclidean
k=58		 Clustering
DBSCAN 1.0 eps=1.4104703215341545
MinPts=208		 Clustering
Hierarchical Clustering 1.0 method=average
k=220		 Clustering
fanny 1.0 k=102
membexp=1.1		 Clustering
k-Means 1.0 k=120
nstart=10		 Clustering
DensityCut 1.0 alpha=0.1220238095238095
K=6		 Clustering
clusterONE 0.0 s=133
d=0.5666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=1.5671892461490604
maxits=5000
convits=350		 Clustering
Markov Clustering 0.0 I=7.737137137137137 Clustering
Transitivity Clustering 1.0 T=1.564051730140754 Clustering
MCODE 1.0 v=0.2
cutoff=1.3059910384575504
haircut=T
fluff=F		 Clustering