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RSNNS (version 0.4-11)

Neural Networks using the Stuttgart Neural Network Simulator (SNNS)

Description

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.

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Install

install.packages('RSNNS')

Monthly Downloads

3,081

Version

0.4-11

License

LGPL (>= 2) | file LICENSE

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Maintainer

Christoph Bergmeir

Last Published

August 10th, 2018

Functions in RSNNS (0.4-11)

SnnsRObject$getInfoHeader

Get an info header of the network.
SnnsRObject$getSiteDefinitions

Get the sites definitions of the network.
SnnsRObject$initializeNet

Initialize the network
art2

Create and train an art2 network
SnnsRObject$resetRSNNS

Reset the SnnsR object.
artmap

Create and train an artmap network
SnnsRObject$predictCurrPatSet

Predict values with a trained net
print.rsnns

Generic print function for rsnns objects
SnnsRObject$getTypeDefinitions

Get the FType definitions of the network.
SnnsRObject$setTTypeUnitsActFunc

Set the activation function for all units of a certain ttype.
SnnsRObject$train

Train a network and test it in every training iteration
SnnsRObject$getAllUnitsTType

Get all units in the net of a certain ttype.
SnnsR-class

The main class of the package
rbf

Create and train a radial basis function (RBF) network
SnnsRObject$somPredictComponentMaps

Calculate the som component maps
SnnsRObject$getUnitDefinitions

Get the unit definitions of the network.
SnnsRObject$setUnitDefaults

Set the unit defaults
readResFile

Rudimentary parser for res files.
SnnsRObject$whereAreResults

Get a list of output units of a net
analyzeClassification

Converts continuous outputs to class labels
dlvq

Create and train a dlvq network
elman

Create and train an Elman network
resolveSnnsRDefine

Resolve a define of the SNNS kernel
decodeClassLabels

Decode class labels to a binary matrix
encodeClassLabels

Encode a matrix of (decoded) class labels
art1

Create and train an art1 network
denormalizeData

Revert data normalization
SnnsRObject$getCompleteWeightMatrix

Get the complete weight matrix.
SnnsRObject$getUnitsByName

Find all units whose name begins with a given prefix.
SnnsRObject$somPredictCurrPatSetWinners

Get most of the relevant results from a som
SnnsRObject$getWeightMatrix

Get the weight matrix between two sets of units
inputColumns

Get the columns that are inputs
getSnnsRDefine

Get a define of the SNNS kernel
exportToSnnsNetFile

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

Create and train a self-organizing map (SOM)
SnnsRObject$somPredictCurrPatSetWinnersSpanTree

Get the spanning tree of the SOM
getSnnsRFunctionTable

Get SnnsR function table
assoz

Create and train an (auto-)associative memory
SnnsRObjectFactory

SnnsR object factory
extractNetInfo

Extract information from a network
confusionMatrix

Computes a confusion matrix
normTrainingAndTestSet

Function to normalize training and test set
SnnsRObjectMethodCaller

Method caller for SnnsR objects
matrixToActMapList

Convert matrix of activations to activation map list
mlp

Create and train a multi-layer perceptron (MLP)
jordan

Create and train a Jordan network
splitForTrainingAndTest

Function to split data into training and test set
plotRegressionError

Plot a regression error plot
predict.rsnns

Generic predict function for rsnns object
plotIterativeError

Plot iterative errors of an rsnns object
train

Internal generic train function for rsnns objects
getNormParameters

Get normalization parameters of the input data
vectorToActMap

Convert a vector to an activation map
plotROC

Plot a ROC curve
rsnnsObjectFactory

Object factory for generating rsnns objects
savePatFile

Save data to a pat file
outputColumns

Get the columns that are targets
weightMatrix

Function to extract the weight matrix of an rsnns object
plotActMap

Plot activation map
normalizeData

Data normalization
setSnnsRSeedValue

DEPRECATED, Set the SnnsR seed value
snnsData

Example data of the package
summary.rsnns

Generic summary function for rsnns objects
toNumericClassLabels

Convert a vector (of class labels) to a numeric vector
rbfDDA

Create and train an RBF network with the DDA algorithm
readPatFile

Load data from a pat file
RSNNS-package

Getting started with the RSNNS package
SnnsRObject$getAllOutputUnits

Get all output units of the net.
SnnsRObject$getAllUnits

Get all units present in the net.
SnnsRObject$createNet

Create a layered network
SnnsRObject$createPatSet

Create a pattern set
SnnsRObject$getAllHiddenUnits

Get all hidden units of the net
SnnsRObject$getAllInputUnits

Get all input units of the net
SnnsRObject$extractNetInfo

Get characteristics of the network.
SnnsRObject$extractPatterns

Extract the current pattern set to a matrix