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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=1
samples=20		 Clustering
Self Organizing Maps 0.931 x=2
y=1		 Clustering
Spectral Clustering 1.0 k=14 Clustering
clusterdp 1.0 k=4
dc=0.5746360569213221		 Clustering
HDBSCAN 1.0 minPts=3
k=4		 Clustering
AGNES 1.0 method=single
metric=euclidean
k=2		 Clustering
c-Means 1.0 k=4
m=1.01		 Clustering
k-Medoids (PAM) 1.0 k=4 Clustering
DIANA 1.0 metric=euclidean
k=1		 Clustering
DBSCAN 1.0 eps=1.1492721138426443
MinPts=1		 Clustering
Hierarchical Clustering 1.0 method=average
k=2		 Clustering
fanny 1.0 k=14
membexp=1.1		 Clustering
k-Means 1.0 k=3
nstart=10		 Clustering
DensityCut 1.0 alpha=0.04761904739176056
K=11		 Clustering
clusterONE 1.0 s=17
d=0.9		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=0.3917973115372651
maxits=5000
convits=500		 Clustering
Markov Clustering 1.0 I=4.619019019019019 Clustering
Transitivity Clustering 1.0 T=0.13961946236963602 Clustering
MCODE 0.852 v=0.7
cutoff=0.5223964153830202
haircut=T
fluff=F		 Clustering