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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=234
samples=20		 Clustering
Self Organizing Maps 1.0 x=33
y=8		 Clustering
Spectral Clustering 0.998 k=34 Clustering
clusterdp 1.0 k=19
dc=1.4758472143145445		 Clustering
HDBSCAN 1.0 minPts=3
k=55		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=27		 Clustering
c-Means 1.0 k=45
m=5.0		 Clustering
k-Medoids (PAM) 1.0 k=214 Clustering
DIANA 1.0 metric=euclidean
k=240		 Clustering
DBSCAN 1.0 eps=0.9838981428763629
MinPts=8		 Clustering
Hierarchical Clustering 1.0 method=average
k=164		 Clustering
fanny 1.0 k=98
membexp=5.0		 Clustering
k-Means 1.0 k=92
nstart=10		 Clustering
DensityCut 1.0 alpha=0.4880952380952381
K=10		 Clustering
clusterONE 0.0 s=64
d=0.13333333333333333		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=14.758472143145443
maxits=3500
convits=500		 Clustering
Markov Clustering 0.0 I=2.6145145145145148 Clustering
Transitivity Clustering 1.0 T=14.714152406979842 Clustering
MCODE 0.991 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering