process_y_sequential

Preprocesses outcome data (<code>y</code>) into a format suitable for Keras models.
Handles both regression (numeric) and classification (factor) outcomes,
including one-hot encoding for classification.

internal

Provides a seamless bridge between 'keras' and the 'tidymodels'
frameworks. It allows for the dynamic creation of 'parsnip' model
specifications for 'keras' models.

David Díaz

kerasnip

A Bridge Between 'keras' and 'tidymodels'

process_y_sequential function

<dl><dt>y</dt>
<dd>A vector of outcomes.</dd>
<dt>is_classification</dt>
<dd>Logical, optional. If <code>TRUE</code>, treats <code>y</code> as
classification. If <code>FALSE</code>, treats as regression. If <code>NULL</code> (default),
it's determined from <code>is.factor(y)</code>.</dd>
<dt>class_levels</dt>
<dd>Character vector, optional. The factor levels for
classification outcomes. If <code>NULL</code> (default), determined from <code>levels(y)</code>.</dd></dl>

Arguments

Process Outcome Input for Keras — process_y_sequential

<dl>

<dt>y</dt>
<dd>A vector of outcomes.</dd>


<dt>is_classification</dt>
<dd>Logical, optional. If <code>TRUE</code>, treats <code>y</code> as
classification. If <code>FALSE</code>, treats as regression. If <code>NULL</code> (default),
it's determined from <code>is.factor(y)</code>.</dd>


<dt>class_levels</dt>
<dd>Character vector, optional. The factor levels for
classification outcomes. If <code>NULL</code> (default), determined from <code>levels(y)</code>.</dd>

</dl>

process_y_sequential: Process Outcome Input for Keras

Description

Usage

Value

Arguments