parallel_batch_snf: Parallel processing form of batch_snf

In metasnf: Meta Clustering with Similarity Network Fusion

Parallel processing form of batch_snf

Description

Parallel processing form of batch_snf

Usage

parallel_batch_snf(
  dl,
  dfl,
  cfl,
  sdf,
  wm,
  similarity_matrix_dir,
  return_sim_mats,
  processes
)

Arguments

dl	A data list.
dfl	An optional nested list containing which distance metric function should be used for the various feature types (continuous, discrete, ordinal, categorical, and mixed). See ?dist_fns_list for details on how to build this.
cfl	List of custom clustering algorithms to apply to the final fused network. See ?clust_fns_list.
sdf	matrix indicating parameters to iterate SNF through.
wm	A matrix containing feature weights to use during distance matrix calculation. See ?weights_matrix for details on how to build this.
similarity_matrix_dir	If specified, this directory will be used to save all generated similarity matrices.
return_sim_mats	If TRUE, function will return a list where the first element is the solutions data frame and the second element is a list of similarity matrices for each row in the sol_df. Default FALSE.
processes	Number of parallel processes used when executing SNF.

Value

The same values as ?batch_snf().

metasnf documentation built on April 3, 2025, 5:40 p.m.