Convert a data list to a similarity matrix through a variety of SNF schemes

Usage

snf_step(
  data_list,
  scheme,
  k = 20,
  alpha = 0.5,
  t = 20,
  cont_dist_fn,
  disc_dist_fn,
  ord_dist_fn,
  cat_dist_fn,
  mix_dist_fn,
  weights_row
)

Arguments

data_list: A nested list of input data from generate_data_list().
scheme: Which SNF system to use to achieve the final fused network.
k: k hyperparameter.
alpha: alpha/eta/sigma hyperparameter.
t: SNF number of iterations hyperparameter.
cont_dist_fn: distance metric function for continuous data.
disc_dist_fn: distance metric function for discrete data.
ord_dist_fn: distance metric function for ordinal data.
cat_dist_fn: distance metric function for categorical data.
mix_dist_fn: distance metric function for mixed data.
weights_row: dataframe row containing feature weights.

Value

fused_network The final fused network (class "matrix", "array") generated by SNF.