SnnsRObject$createNet

SnnsR__createNet

createNet,SnnsR-method

a vector of integers that represents the number of units in each layer, including input and output layer

unitsPerLayer

if <code>TRUE</code>, the network is fully connected as a feed-forward network. If <code>FALSE</code>, 
no connections are created

fullyConnectedFeedForward

iNames

oNames


This function creates a layered network in the given SnnsR object.
This is an SnnsR low-level function. You may want to have a look 
at <code><a rd-options="" href="/link/SnnsR-class?package=RSNNS&version=0.4-9" data-mini-rdoc="RSNNS::SnnsR-class">SnnsR-class</a></code> to find out how to properly use it.


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)

SnnsRObject$createNet function


This function creates a layered network in the given SnnsR object.
This is an SnnsR low-level function. You may want to have a look 
at <code><a rd-options='' href='SnnsR-class'>SnnsR-class</a></code> to find out how to properly use it.


SnnsRObject$createNet: Create a layered network

Description

Usage

Arguments

See Also

Examples