.defaultScalarArguments
                        Define the default arguments
AffinityParam-class     Affinity propogation
AgnesParam-class        Agglomerative nesting
BlusterParam-class      The BlusterParam class
ClaraParam-class        Clustering Large Applications
DbscanParam-class       Density-based clustering with DBSCAN
DianaParam-class        Divisive analysis clustering
DmmParam-class          Dirichlet multinomial mixture clustering
FixedNumberParam-class
                        The FixedNumberParam class
HclustParam-class       Hierarchical clustering
HierarchicalParam-class
                        The HierarchicalParam class
KmeansParam-class       K-means clustering
MbkmeansParam-class     Mini-batch k-means clustering
NNGraphParam-class      Graph-based clustering
PamParam-class          Partitioning around medoids
SomParam-class          Clustering with self-organizing maps
TwoStepParam-class      Two step clustering with vector quantization
approxSilhouette        Approximate silhouette width
bootstrapStability      Assess cluster stability by bootstrapping
clusterRMSD             Compute the RMSD per cluster
clusterRows             Cluster rows of a matrix
clusterSweep            Clustering parameter sweeps
compareClusterings      Compare pairs of clusterings
linkClusters            Create a graph between different clusterings
makeSNNGraph            Build a nearest-neighbor graph
mergeCommunities        Merge communities from graph-based clustering
neighborPurity          Compute neighborhood purity
nestedClusters          Map nested clusterings
pairwiseModularity      Compute pairwise modularity
pairwiseRand            Compute pairwise Rand indices
