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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=100
samples=20		 Clustering
Self Organizing Maps 1.0 x=33
y=8		 Clustering
Spectral Clustering 0.998 k=34 Clustering
clusterdp 1.0 k=12
dc=9.838981428763628		 Clustering
HDBSCAN 1.0 minPts=5
k=128		 Clustering
AGNES 1.0 method=ward
metric=euclidean
k=16		 Clustering
c-Means 1.0 k=14
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=143 Clustering
DIANA 1.0 metric=euclidean
k=233		 Clustering
DBSCAN 1.0 eps=3.44364350006727
MinPts=32		 Clustering
Hierarchical Clustering 1.0 method=single
k=182		 Clustering
fanny 1.0 k=90
membexp=1.1		 Clustering
k-Means 1.0 k=92
nstart=10		 Clustering
DensityCut 1.0 alpha=0.42857142857142855
K=12		 Clustering
clusterONE 0.0 s=48
d=0.9		 Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=11.068854107359083
maxits=5000
convits=500		 Clustering
Markov Clustering 0.0 I=1.6523523523523527 Clustering
Transitivity Clustering 1.0 T=12.926589714967228 Clustering
MCODE 0.991 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering