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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=230
samples=20		 Clustering
Self Organizing Maps 1.0 x=385
y=239		 Clustering
Spectral Clustering 0.999 k=24 Clustering
clusterdp 0.991 k=24
dc=3.6781585066443236		 Clustering
HDBSCAN 1.0 minPts=95
k=399		 Clustering
AGNES 1.0 method=complete
metric=euclidean
k=75		 Clustering
c-Means 1.0 k=394
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=324 Clustering
DIANA 1.0 metric=euclidean
k=379		 Clustering
DBSCAN 1.0 eps=11.034475519932972
MinPts=253		 Clustering
Hierarchical Clustering 1.0 method=average
k=342		 Clustering
fanny 1.0 k=162
membexp=1.1		 Clustering
k-Means 1.0 k=204
nstart=10		 Clustering
DensityCut 0.935 alpha=0.12152777777777776
K=3		 Clustering
clusterONE 0.0 s=14
d=0.23333333333333334		 Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=36.781585066443235
maxits=5000
convits=500		 Clustering
Markov Clustering 0.0 I=6.463163163163164 Clustering
Transitivity Clustering 1.0 T=36.22930901439454 Clustering
MCODE 0.996 v=0.1
cutoff=32.183886933137835
haircut=T
fluff=T		 Clustering