SnnsRObject$extractPatterns

SnnsR__extractPatterns

extractPatterns,SnnsR-method

<p>SnnsR low-level function that extracts all patterns of the current pattern set and
returns them as a matrix. Columns are named with the prefix "in" or "out", respectively.</p>

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)

Jos<c3><a9> M. Ben<c3><ad>tez

Andreas Zell

Niels Mache

G<c3><bc>nter Mamier

Michael Vogt

Sven D<c3><b6>ring

Ralf H<c3><bc>bner

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$extractPatterns function

Extract the current pattern set to a matrix — SnnsRObject$extractPatterns

Extract the current pattern set to a matrix

SnnsRObject$extractPatterns: Extract the current pattern set to a matrix

Description

Usage

Arguments

Value