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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=13 Clustering
clusterdp 1.0 k=8
dc=13.943265184310308		 Clustering
HDBSCAN 1.0 minPts=86
k=1		 Clustering
AGNES 1.0 method=single
metric=euclidean
k=11		 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=3		 Clustering
DBSCAN 1.0 eps=0.9295510122873538
MinPts=220		 Clustering
Hierarchical Clustering 1.0 method=average
k=2		 Clustering
fanny 1.0 k=2
membexp=5.0		 Clustering
k-Means 1.0 k=2
nstart=10		 Clustering
DensityCut 1.0 alpha=0.29761904761904756
K=48		 Clustering
clusterONE 1.0 s=240
d=0.1		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=0.0
maxits=2750
convits=500		 Clustering
Markov Clustering 1.0 I=3.7014014014014016 Clustering
Transitivity Clustering 1.0 T=0.1814438912873213 Clustering
MCODE 0.909 v=0.6
cutoff=12.781326418951116
haircut=T
fluff=F		 Clustering