subnetwork_init: Initializes a Subnetwork based on the Processed Additive...

In deepregression: Fitting Deep Distributional Regression

Initializes a Subnetwork based on the Processed Additive Predictor

Description

Initializes a Subnetwork based on the Processed Additive Predictor

Usage

subnetwork_init(
  pp,
  deep_top = NULL,
  orthog_fun = orthog_tf,
  split_fun = split_model,
  shared_layers = NULL,
  param_nr = 1,
  selectfun_in = function(pp) pp[[param_nr]],
  selectfun_lay = function(pp) pp[[param_nr]],
  gaminputs,
  summary_layer = layer_add_identity
)

Arguments

pp	list of processed predictor lists from processor
deep_top	keras layer if the top part of the deep network after orthogonalization is different to the one extracted from the provided network
orthog_fun	function used for orthogonalization
split_fun	function to split the network to extract head
shared_layers	list defining shared weights within one predictor; each list item is a vector of characters of terms as given in the parameter formula
param_nr	integer number for the distribution parameter
selectfun_in, selectfun_lay	functions defining which subset of pp to take as inputs and layers for this subnetwork; per default the param_nr's entry
gaminputs	input tensors for gam terms
summary_layer	keras layer that combines inputs (typically adding or concatenating)

Value

returns a list of input and output for this additive predictor

deepregression documentation built on Jan. 18, 2023, 1:11 a.m.