orthog_control {deepregression} R Documentation

## 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

[Package deepregression version 1.0.0 Index]