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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=204
samples=20		 Clustering
Self Organizing Maps 1.0 x=26
y=133		 Clustering
Spectral Clustering 0.996 k=25 Clustering
clusterdp 1.0 k=17
dc=0.8880739061511342		 Clustering
HDBSCAN 1.0 minPts=250
k=1		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=12		 Clustering
c-Means 1.0 k=4
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=233 Clustering
DIANA 1.0 metric=euclidean
k=92		 Clustering
DBSCAN 1.0 eps=1.5149496046107584
MinPts=183		 Clustering
Hierarchical Clustering 1.0 method=single
k=144		 Clustering
fanny 1.0 k=97
membexp=5.0		 Clustering
k-Means 1.0 k=196
nstart=10		 Clustering
DensityCut 1.0 alpha=0.05952380952380952
K=25		 Clustering
clusterONE 0.0 s=191
d=0.4		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=0.3917973115372651
maxits=2000
convits=350		 Clustering
Markov Clustering 0.0 I=2.578878878878879 Clustering
Transitivity Clustering 1.0 T=1.4558074278541822 Clustering
MCODE 1.0 v=0.4
cutoff=1.3059910384575504
haircut=F
fluff=F		 Clustering