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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=1
samples=20		 Clustering
Self Organizing Maps 0.931 x=2
y=1		 Clustering
Spectral Clustering 1.0 k=14 Clustering
clusterdp 1.0 k=2
dc=0.6268756984596242		 Clustering
HDBSCAN 1.0 minPts=2
k=4		 Clustering
AGNES 1.0 method=ward
metric=euclidean
k=3		 Clustering
c-Means 1.0 k=3
m=5.0		 Clustering
k-Medoids (PAM) 1.0 k=4 Clustering
DIANA 1.0 metric=euclidean
k=65		 Clustering
DBSCAN 1.0 eps=0.20895856615320804
MinPts=17		 Clustering
Hierarchical Clustering 1.0 method=average
k=5		 Clustering
fanny 1.0 k=12
membexp=1.1		 Clustering
k-Means 1.0 k=3
nstart=10		 Clustering
DensityCut 1.0 alpha=0.045712425595238096
K=12		 Clustering
clusterONE 1.0 s=117
d=0.7666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=0.7835946230745302
maxits=2750
convits=500		 Clustering
Markov Clustering 1.0 I=5.741541541541543 Clustering
Transitivity Clustering 1.0 T=0.756141358001849 Clustering
MCODE 0.852 v=0.6
cutoff=0.5223964153830202
haircut=T
fluff=T		 Clustering