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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=39
samples=20		 Clustering
Self Organizing Maps 1.0 x=2
y=208		 Clustering
Spectral Clustering 1.0 k=86 Clustering
clusterdp 1.0 k=9
dc=18.184652869934034		 Clustering
HDBSCAN 1.0 minPts=149
k=312		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=39		 Clustering
c-Means 1.0 k=312
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=253 Clustering
DIANA 1.0 metric=euclidean
k=66		 Clustering
DBSCAN 1.0 eps=0.0
MinPts=11		 Clustering
Hierarchical Clustering 1.0 method=single
k=233		 Clustering
fanny 1.0 k=45
membexp=1.1		 Clustering
k-Means 1.0 k=136
nstart=10		 Clustering
DensityCut 1.0 alpha=0.06696428571428571
K=3		 Clustering
clusterONE 0.0 s=94
d=0.8		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=30.307754783223388
maxits=4250
convits=200		 Clustering
Markov Clustering 0.0 I=2.7837837837837838 Clustering
Transitivity Clustering 1.0 T=26.727859823843648 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=T		 Clustering