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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=147
samples=20		 Clustering
Self Organizing Maps 1.0 x=33
y=8		 Clustering
Spectral Clustering 0.998 k=34 Clustering
clusterdp 1.0 k=16
dc=10.82287957163999		 Clustering
HDBSCAN 1.0 minPts=8
k=176		 Clustering
AGNES 1.0 method=ward
metric=euclidean
k=51		 Clustering
c-Means 1.0 k=220
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=218 Clustering
DIANA 1.0 metric=euclidean
k=233		 Clustering
DBSCAN 1.0 eps=0.9838981428763629
MinPts=8		 Clustering
Hierarchical Clustering 1.0 method=single
k=147		 Clustering
fanny 1.0 k=79
membexp=1.1		 Clustering
k-Means 1.0 k=216
nstart=10		 Clustering
DensityCut 1.0 alpha=0.5464285714285714
K=12		 Clustering
clusterONE 0.0 s=40
d=0.43333333333333335		 Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=14.758472143145443
maxits=2000
convits=200		 Clustering
Markov Clustering 0.0 I=2.071071071071071 Clustering
Transitivity Clustering 1.0 T=14.610739689260104 Clustering
MCODE 0.991 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering