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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 0.987 x=2
y=1		 Clustering
Spectral Clustering 1.0 k=17 Clustering
clusterdp 1.0 k=9
dc=11.619387653591923		 Clustering
HDBSCAN 1.0 minPts=45
k=6		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=1		 Clustering
c-Means 1.0 k=2
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=8 Clustering
DIANA 1.0 metric=euclidean
k=12		 Clustering
DBSCAN 1.0 eps=0.9295510122873538
MinPts=240		 Clustering
Hierarchical Clustering 1.0 method=average
k=2		 Clustering
fanny 1.0 k=5
membexp=2.0		 Clustering
k-Means 1.0 k=7
nstart=10		 Clustering
DensityCut 1.0 alpha=0.1976190476190476
K=60		 Clustering
clusterONE 1.0 s=160
d=0.4		 Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=0.0
maxits=2000
convits=200		 Clustering
Markov Clustering 1.0 I=4.155755755755756 Clustering
Transitivity Clustering 1.0 T=0.16748666888060432 Clustering
MCODE 0.909 v=0.6
cutoff=12.781326418951116
haircut=T
fluff=F		 Clustering