[.ruta_network

Implementation of several unsupervised neural networks,
from building their architecture to their training and evaluation. Available
networks are auto-encoders including their main variants: sparse, contractive,
denoising, robust and variational, as described in Charte et al. (2018)
<doi:10.1016/j.inffus.2017.12.007>.

David Charte

ruta

Implementation of Unsupervised Neural Architectures

Francisco Charte

Francisco Herrera

[.ruta_network function

<dl><dt>net</dt>
<dd>A <code>"ruta_network"</code> object</dd>
<dt>index</dt>
<dd>An integer vector of indices of layers to be extracted</dd></dl>

Arguments

Access subnetworks of a network — [.ruta_network

<dl>

<dt>net</dt>
<dd>A <code>"ruta_network"</code> object</dd>


<dt>index</dt>
<dd>An integer vector of indices of layers to be extracted</dd>

</dl>

[.ruta_network: Access subnetworks of a network

Description

Usage

Value

Arguments

Examples