extractNetInfo

This function generates a list of data.frames containing the most important information 
that defines a network, in a format that is easy to use. To get the full definition in 
the original SNNS format, use <code>summary.rsnns</code> or <code>exportToSnnsNetFile</code> 
instead.

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

extractNetInfo function

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

Arguments

Extract information from a network — extractNetInfo

<dl>

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

</dl>

Extract information from a network

extractNetInfo: Extract information from a network

Description

Usage

Value

Arguments

Details

See Also