exportToSnnsNetFile

the <code><a rd-options="" href="/link/rsnns?package=RSNNS&version=0.4-14" data-mini-rdoc="RSNNS::rsnns">rsnns</a></code> object

object

path and filename to be written to

filename

name that is given to the network in the file

netname

Export the net that is present in the <code>rsnns</code> object in the 
original (.net) SNNS file format.

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

exportToSnnsNetFile function

<dl><dt>object</dt>
<dd>the <code>rsnns</code> object</dd>
<dt>filename</dt>
<dd>path and filename to be written to</dd>
<dt>netname</dt>
<dd>name that is given to the network in the file</dd></dl>

Arguments

Export the net to a file in the original SNNS file format — exportToSnnsNetFile

<dl>

<dt>object</dt>
<dd>the <code>rsnns</code> object</dd>


<dt>filename</dt>
<dd>path and filename to be written to</dd>


<dt>netname</dt>
<dd>name that is given to the network in the file</dd>

</dl>

Export the net to a file in the original SNNS file format

exportToSnnsNetFile: Export the net to a file in the original SNNS file format

Description

Usage

Arguments