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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=2
samples=20		 Clustering
Self Organizing Maps 0.987 x=2
y=1		 Clustering
Spectral Clustering 1.0 k=12 Clustering
clusterdp 1.0 k=3
dc=1.3943265184310307		 Clustering
HDBSCAN 1.0 minPts=229
k=1		 Clustering
AGNES 1.0 method=single
metric=euclidean
k=1		 Clustering
c-Means 1.0 k=2
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=2 Clustering
DIANA 1.0 metric=euclidean
k=7		 Clustering
DBSCAN 1.0 eps=0.0
MinPts=200		 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=0.1976190476190476
K=119		 Clustering
clusterONE 1.0 s=100
d=0.3333333333333333		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=0.0
maxits=2750
convits=500		 Clustering
Markov Clustering 1.0 I=9.171471471471472 Clustering
Transitivity Clustering 1.0 T=1.0328344580970599 Clustering
MCODE 0.909 v=0.5
cutoff=12.781326418951116
haircut=T
fluff=T		 Clustering