orthog_control {deepregression}

Options for orthogonalization

Description

Options for orthogonalization

Usage

orthog_control(
  split_fun = split_model,
  orthog_type = c("tf", "manual"),
  orthogonalize = options()$orthogonalize,
  identify_intercept = options()$identify_intercept,
  deep_top = NULL,
  orthog_fun = NULL,
  deactivate_oz_at_test = TRUE
)

Arguments

split_fun

a function separating the deep neural network in two parts so that the orthogonalization can be applied to the first part before applying the second network part; per default, the function split_model is used which assumes a dense layer as penultimate layer and separates the network into a first part without this last layer and a second part only consisting of a single dense layer that is fed into the output layer

orthog_type

one of two options; If "manual", the QR decomposition is calculated before model fitting, otherwise ("tf") a QR is calculated in each batch iteration via TF. The first only works well for larger batch sizes or ideally batch_size == NROW(y).

orthogonalize

logical; if set to TRUE, automatic orthogonalization is activated

identify_intercept

whether to orthogonalize the deep network w.r.t. the intercept to make the intercept identifiable

deep_top

function; optional function to put on top of the deep network instead of splitting the function using split_fun

orthog_fun

function; for custom orthogonaliuation. if NULL, orthog_type is used to define the function that computes the orthogonalization

deactivate_oz_at_test

logical; whether to deactive the orthogonalization cell at test time when using orthog_tf for orthog_fun (the default).

Value

Returns a list with options