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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=161
samples=20		 Clustering
Self Organizing Maps 1.0 x=157
y=197		 Clustering
Spectral Clustering 1.0 k=39 Clustering
clusterdp 1.0 k=4
dc=16.164135884385807		 Clustering
HDBSCAN 1.0 minPts=25
k=146		 Clustering
AGNES 1.0 method=ward
metric=euclidean
k=224		 Clustering
c-Means 1.0 k=286
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=166 Clustering
DIANA 1.0 metric=euclidean
k=290		 Clustering
DBSCAN 1.0 eps=29.297496290449274
MinPts=260		 Clustering
Hierarchical Clustering 1.0 method=complete
k=242		 Clustering
fanny 1.0 k=138
membexp=5.0		 Clustering
k-Means 1.0 k=247
nstart=10		 Clustering
DensityCut 1.0 alpha=0.059522787729899086
K=6		 Clustering
clusterONE 0.0 s=73
d=0.9666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=15.153877391611694
maxits=3500
convits=200		 Clustering
Markov Clustering 0.0 I=4.111211211211211 Clustering
Transitivity Clustering 1.0 T=28.457131117781316 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=F		 Clustering