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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=78
samples=20		 Clustering
Self Organizing Maps 1.0 x=134
y=67		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=18
dc=0.10447928307660402		 Clustering
HDBSCAN 1.0 minPts=36
k=155		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=213		 Clustering
c-Means 1.0 k=4
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=247 Clustering
DIANA 1.0 metric=euclidean
k=45		 Clustering
DBSCAN 1.0 eps=1.0970324723043423
MinPts=191		 Clustering
Hierarchical Clustering 1.0 method=average
k=76		 Clustering
fanny 1.0 k=79
membexp=2.0		 Clustering
k-Means 1.0 k=128
nstart=10		 Clustering
DensityCut 1.0 alpha=0.04507688492063492
K=10		 Clustering
clusterONE 0.0 s=158
d=0.16666666666666666		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=1.1753919346117954
maxits=3500
convits=275		 Clustering
Markov Clustering 0.0 I=2.48978978978979 Clustering
Transitivity Clustering 1.0 T=1.4181572357545051 Clustering
MCODE 1.0 v=0.6
cutoff=1.2406914865346728
haircut=T
fluff=T		 Clustering