orthog_control: Options for orthogonalization

In deepregression: Fitting Deep Distributional Regression

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
)

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

Value

Returns a list with options

deepregression documentation built on Oct. 5, 2021, 1:06 a.m.