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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=207
samples=20		 Clustering
Self Organizing Maps 1.0 x=49
y=32		 Clustering
Spectral Clustering 0.998 k=34 Clustering
clusterdp 1.0 k=6
dc=5.411439785819995		 Clustering
HDBSCAN 1.0 minPts=5
k=128		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=13		 Clustering
c-Means 1.0 k=235
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=231 Clustering
DIANA 1.0 metric=euclidean
k=232		 Clustering
DBSCAN 1.0 eps=8.855083285887266
MinPts=176		 Clustering
Hierarchical Clustering 1.0 method=complete
k=22		 Clustering
fanny 1.0 k=82
membexp=1.1		 Clustering
k-Means 1.0 k=155
nstart=10		 Clustering
DensityCut 1.0 alpha=0.5792410714285714
K=12		 Clustering
clusterONE 0.0 s=72
d=0.7		 Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=14.758472143145443
maxits=5000
convits=200		 Clustering
Markov Clustering 0.0 I=2.659059059059059 Clustering
Transitivity Clustering 1.0 T=14.182315572992618 Clustering
MCODE 0.991 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering