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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=195
samples=20		 Clustering
Self Organizing Maps 1.0 x=33
y=8		 Clustering
Spectral Clustering 0.998 k=34 Clustering
clusterdp 1.0 k=17
dc=3.9355925715054516		 Clustering
HDBSCAN 1.0 minPts=15
k=80		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=237		 Clustering
c-Means 1.0 k=66
m=1.5		 Clustering
k-Medoids (PAM) 1.0 k=92 Clustering
DIANA 1.0 metric=euclidean
k=116		 Clustering
DBSCAN 1.0 eps=0.0
MinPts=40		 Clustering
Hierarchical Clustering 1.0 method=average
k=65		 Clustering
fanny 1.0 k=127
membexp=1.1		 Clustering
k-Means 1.0 k=56
nstart=10		 Clustering
DensityCut 1.0 alpha=0.6190476190476191
K=12		 Clustering
clusterONE 0.0 s=72
d=0.1		 Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=14.758472143145443
maxits=2000
convits=500		 Clustering
Markov Clustering 0.0 I=2.8105105105105106 Clustering
Transitivity Clustering 1.0 T=13.916397155999006 Clustering
MCODE 0.991 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering