prepare_data_torch

Function to additionally prepare data for fit process (torch)

Allows for the specification of semi-structured deep distributional regression models which are fitted in a neural network as
proposed by Ruegamer et al. (2023) <doi:10.18637/jss.v105.i02>.
Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model.

David Ruegamer

deepregression

Fitting Deep Distributional Regression

Christopher Marquardt

Laetitia Frost

Florian Pfisterer

Philipp Baumann

Chris Kolb

Lucas Kook

prepare_data_torch function

<dl><dt>pfc</dt>
<dd>list of processor transformed formulas</dd>
<dt>input_x</dt>
<dd>output of prepare_data()</dd>
<dt>target</dt>
<dd>target values</dd>
<dt>object</dt>
<dd>a deepregression object</dd></dl>

Arguments

Function to additionally prepare data for fit process (torch) — prepare_data_torch

<dl>

<dt>pfc</dt>
<dd>list of processor transformed formulas</dd>


<dt>input_x</dt>
<dd>output of prepare_data()</dd>


<dt>target</dt>
<dd>target values</dd>


<dt>object</dt>
<dd>a deepregression object</dd>

</dl>

prepare_data_torch: Function to additionally prepare data for fit process (torch)

Description

Usage

Value

Arguments