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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=243
samples=20		 Clustering
Self Organizing Maps 1.0 x=126
y=63		 Clustering
Spectral Clustering 1.0 k=26 Clustering
clusterdp 1.0 k=18
dc=16.164135884385807		 Clustering
HDBSCAN 1.0 minPts=4
k=33		 Clustering
AGNES 1.0 method=ward
metric=euclidean
k=69		 Clustering
c-Means 1.0 k=127
m=5.0		 Clustering
k-Medoids (PAM) 1.0 k=178 Clustering
DIANA 1.0 metric=euclidean
k=219		 Clustering
DBSCAN 1.0 eps=29.297496290449274
MinPts=260		 Clustering
Hierarchical Clustering 1.0 method=complete
k=129		 Clustering
fanny 1.0 k=120
membexp=5.0		 Clustering
k-Means 1.0 k=306
nstart=10		 Clustering
DensityCut 1.0 alpha=0.01984126984126984
K=7		 Clustering
clusterONE 0.0 s=156
d=0.4666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=30.307754783223388
maxits=3500
convits=425		 Clustering
Markov Clustering 0.0 I=2.1957957957957963 Clustering
Transitivity Clustering 1.0 T=26.242450337826057 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=T
fluff=T		 Clustering