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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=291
samples=20		 Clustering
Self Organizing Maps 1.0 x=630
y=263		 Clustering
Spectral Clustering 1.0 k=118 Clustering
clusterdp 1.0 k=20
dc=2.587697389143054		 Clustering
HDBSCAN 1.0 minPts=450
k=788		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=394		 Clustering
c-Means 1.0 k=7
m=5.0		 Clustering
k-Medoids (PAM) 1.0 k=519 Clustering
DIANA 1.0 metric=euclidean
k=776		 Clustering
DBSCAN 1.0 eps=0.0
MinPts=1		 Clustering
Hierarchical Clustering 1.0 method=average
k=690		 Clustering
fanny 1.0 k=160
membexp=1.1		 Clustering
k-Means 1.0 k=335
nstart=10		 Clustering
DensityCut 1.0 alpha=1.52587890625E-5
K=10		 Clustering
clusterONE 0.0 s=184
d=0.26666666666666666		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=38.815460837145814
maxits=3500
convits=275		 Clustering
Markov Clustering 0.0 I=7.986586586586587 Clustering
Transitivity Clustering 1.0 T=36.095658776484946 Clustering
MCODE 1.0 v=0.9
cutoff=35.58083910071699
haircut=F
fluff=F		 Clustering