extractNetInfo

the <code><a rd-options="" href="/link/rsnns?package=RSNNS&version=0.4-9" data-mini-rdoc="RSNNS::rsnns">rsnns</a></code> object

object


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><a rd-options="" href="/link/summary.rsnns?package=RSNNS&version=0.4-9" data-mini-rdoc="RSNNS::summary.rsnns">summary.rsnns</a></code> or <code><a rd-options="" href="/link/exportToSnnsNetFile?package=RSNNS&version=0.4-9" data-mini-rdoc="RSNNS::exportToSnnsNetFile">exportToSnnsNetFile</a></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 in R using the Stuttgart Neural Network
Simulator (SNNS)

extractNetInfo function

the <code><a rd-options='' href='rsnns'>rsnns</a></code> object


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><a rd-options='' href='summary.rsnns'>summary.rsnns</a></code> or <code><a rd-options='' href='exportToSnnsNetFile'>exportToSnnsNetFile</a></code> 
instead.


extractNetInfo: Extract information from a network

Description

Usage

Arguments

Value

Details

See Also