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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=32
samples=20		 Clustering
Self Organizing Maps 1.0 x=250
y=250		 Clustering
Spectral Clustering 1.0 k=18 Clustering
clusterdp 1.0 k=19
dc=0.522160816583292		 Clustering
HDBSCAN 1.0 minPts=36
k=155		 Clustering
AGNES 1.0 method=complete
metric=euclidean
k=9		 Clustering
c-Means 1.0 k=39
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=109 Clustering
DIANA 1.0 metric=euclidean
k=68		 Clustering
DBSCAN 1.0 eps=1.8275628580415222
MinPts=200		 Clustering
Hierarchical Clustering 1.0 method=average
k=244		 Clustering
fanny 1.0 k=74
membexp=5.0		 Clustering
k-Means 1.0 k=168
nstart=10		 Clustering
DensityCut 1.0 alpha=0.9875
K=6		 Clustering
clusterONE 0.0 s=67
d=0.5		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=3.9162061243746904
maxits=3500
convits=275		 Clustering
Markov Clustering 0.0 I=4.227027027027027 Clustering
Transitivity Clustering 1.0 T=3.6731582968359207 Clustering
MCODE 0.999 v=0.6
cutoff=3.589855614010133
haircut=T
fluff=T		 Clustering