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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=101
samples=20		 Clustering
Self Organizing Maps 1.0 x=33
y=8		 Clustering
Spectral Clustering 0.998 k=34 Clustering
clusterdp 1.0 k=23
dc=11.314828643078174		 Clustering
HDBSCAN 1.0 minPts=35
k=148		 Clustering
AGNES 1.0 method=complete
metric=euclidean
k=9		 Clustering
c-Means 1.0 k=23
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=218 Clustering
DIANA 1.0 metric=euclidean
k=232		 Clustering
DBSCAN 1.0 eps=0.9838981428763629
MinPts=240		 Clustering
Hierarchical Clustering 1.0 method=average
k=220		 Clustering
fanny 1.0 k=96
membexp=2.0		 Clustering
k-Means 1.0 k=172
nstart=10		 Clustering
DensityCut 1.0 alpha=0.6714285714285714
K=6		 Clustering
clusterONE 0.0 s=96
d=0.8666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=14.758472143145443
maxits=3500
convits=200		 Clustering
Markov Clustering 0.0 I=2.1156156156156154 Clustering
Transitivity Clustering 1.0 T=14.108449346049948 Clustering
MCODE 0.991 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering