SnnsRObject$initializeNet

SnnsR__initializeNet

initializeNet,SnnsR-method

the parameters of the initialization function

parameterInArray

the name of the initialization function

initFunc

This SnnsR low-level function masks the SNNS kernel function of the same name
to allow for both giving the initialization function
directly in the call or to use the one that is currently set.

The Stuttgart Neural Network Simulator (SNNS) is a library
containing many standard implementations of neural networks. This
package wraps the SNNS functionality to make it available from
within R. Using the 'RSNNS' low-level interface, all of the
algorithmic functionality and flexibility of SNNS can be accessed.
Furthermore, the package contains a convenient high-level
interface, so that the most common neural network topologies and
learning algorithms integrate seamlessly into R.

Christoph Bergmeir

RSNNS

Neural Networks using the Stuttgart Neural Network Simulator
(SNNS)

José M. Benítez

Andreas Zell

Niels Mache

Günter Mamier

Michael Vogt

Sven Döring

Ralf Hübner

Kai-Uwe Herrmann

Tobias Soyez

Michael Schmalzl

Tilman Sommer

Artemis Hatzigeorgiou

Dietmar Posselt

Tobias Schreiner

Bernward Kett

Martin Reczko

Martin Riedmiller

Mark Seemann

Marcus Ritt

Jamie DeCoster

Jochen Biedermann

Joachim Danz

Christian Wehrfritz

Patrick Kursawe

Andre El-Ama

SnnsRObject$initializeNet function

<dl><dt>parameterInArray</dt>
<dd>the parameters of the initialization function</dd>
<dt>initFunc</dt>
<dd>the name of the initialization function</dd></dl>

Arguments

Initialize the network — SnnsRObject$initializeNet

<dl>

<dt>parameterInArray</dt>
<dd>the parameters of the initialization function</dd>


<dt>initFunc</dt>
<dd>the name of the initialization function</dd>

</dl>

Initialize the network

SnnsRObject$initializeNet: Initialize the network

Description

Usage

Arguments