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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=287
samples=20		 Clustering
Self Organizing Maps 1.0 x=293
y=213		 Clustering
Spectral Clustering 0.999 k=24 Clustering
clusterdp 0.991 k=24
dc=3.6781585066443236		 Clustering
HDBSCAN 1.0 minPts=38
k=361		 Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=321		 Clustering
c-Means 1.0 k=390
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=398 Clustering
DIANA 1.0 metric=euclidean
k=248		 Clustering
DBSCAN 1.0 eps=1.2260528355481077
MinPts=359		 Clustering
Hierarchical Clustering 1.0 method=average
k=384		 Clustering
fanny 1.0 k=73
membexp=2.0		 Clustering
k-Means 1.0 k=142
nstart=10		 Clustering
DensityCut 0.935 alpha=0.19593253968253968
K=3		 Clustering
clusterONE 0.0 s=345
d=0.7666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=36.781585066443235
maxits=3500
convits=275		 Clustering
Markov Clustering 0.0 I=5.982082082082083 Clustering
Transitivity Clustering 1.0 T=36.781585066443235 Clustering
MCODE 0.996 v=0.1
cutoff=32.183886933137835
haircut=F
fluff=T		 Clustering