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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=6
dc=3.7182040491494153		 Clustering
HDBSCAN 1.0 minPts=23
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=2		 Clustering
DBSCAN 1.0 eps=0.4647755061436769
MinPts=340		 Clustering
Hierarchical Clustering 1.0 method=average
k=2		 Clustering
fanny 1.0 k=12
membexp=5.0		 Clustering
k-Means 1.0 k=7
nstart=10		 Clustering
DensityCut 1.0 alpha=0.4309523809523809
K=60		 Clustering
clusterONE 1.0 s=140
d=0.7		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=0.0
maxits=2750
convits=500		 Clustering
Markov Clustering 1.0 I=10.0 Clustering
Transitivity Clustering 1.0 T=8.276632887183196 Clustering
MCODE 0.909 v=0.5
cutoff=12.781326418951116
haircut=F
fluff=F		 Clustering