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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=82
samples=20		 Clustering
Self Organizing Maps 1.0 x=233
y=233		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=19
dc=1.4627099630724563		 Clustering
HDBSCAN 1.0 minPts=10
k=8		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=43		 Clustering
c-Means 1.0 k=4
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=10 Clustering
DIANA 1.0 metric=euclidean
k=7		 Clustering
DBSCAN 1.0 eps=0.2611982076915101
MinPts=17		 Clustering
Hierarchical Clustering 1.0 method=single
k=87		 Clustering
fanny 1.0 k=60
membexp=5.0		 Clustering
k-Means 1.0 k=135
nstart=10		 Clustering
DensityCut 1.0 alpha=0.04507688492063492
K=10		 Clustering
clusterONE 0.0 s=167
d=0.5333333333333333		 Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=1.5671892461490604
maxits=2750
convits=275		 Clustering
Markov Clustering 0.0 I=2.7125125125125127 Clustering
Transitivity Clustering 1.0 T=1.0981306029072495 Clustering
MCODE 1.0 v=0.1
cutoff=1.1753919346117954
haircut=T
fluff=T		 Clustering