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RSNNS (version 0.4-17)

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.packages('RSNNS')

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2,234

Version

0.4-17

License

LGPL (>= 2) | file LICENSE

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Last Published

November 30th, 2023

Functions in RSNNS (0.4-17)

SnnsRObject$somPredictComponentMaps

Calculate the som component maps
elman

Create and train an Elman network
dlvq

Create and train a dlvq network
SnnsRObject$createPatSet

Create a pattern set
SnnsRObject$getAllUnits

Get all units present in the net.
SnnsRObject$somPredictCurrPatSetWinners

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

Get the complete weight matrix.
SnnsRObject$somPredictCurrPatSetWinnersSpanTree

Get the spanning tree of the SOM
getSnnsRFunctionTable

Get SnnsR function table
SnnsRObject$getAllUnitsTType

Get all units in the net of a certain ttype.
getSnnsRDefine

Get a define of the SNNS kernel
SnnsRObjectFactory

SnnsR object factory
plotROC

Plot a ROC curve
plotIterativeError

Plot iterative errors of an rsnns object
normTrainingAndTestSet

Function to normalize training and test set
rbf

Create and train a radial basis function (RBF) network
print.rsnns

Generic print function for rsnns objects
assoz

Create and train an (auto-)associative memory
confusionMatrix

Computes a confusion matrix
encodeClassLabels

Encode a matrix of (decoded) class labels
exportToSnnsNetFile

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

Get the columns that are inputs
SnnsRObject$extractNetInfo

Get characteristics of the network.
SnnsRObjectMethodCaller

Method caller for SnnsR objects
summary.rsnns

Generic summary function for rsnns objects
SnnsRObject$extractPatterns

Extract the current pattern set to a matrix
resolveSnnsRDefine

Resolve a define of the SNNS kernel
readResFile

Rudimentary parser for res files.
weightMatrix

Function to extract the weight matrix of an rsnns object
SnnsRObject$getTypeDefinitions

Get the FType definitions of the network.
normalizeData

Data normalization
rbfDDA

Create and train an RBF network with the DDA algorithm
readPatFile

Load data from a pat file
SnnsRObject$getUnitDefinitions

Get the unit definitions of the network.
SnnsRObject$setTTypeUnitsActFunc

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

Reset the SnnsR object.
jordan

Create and train a Jordan network
toNumericClassLabels

Convert a vector (of class labels) to a numeric vector
art2

Create and train an art2 network
getNormParameters

Get normalization parameters of the input data
SnnsRObject$train

Train a network and test it in every training iteration
artmap

Create and train an artmap network
extractNetInfo

Extract information from a network
SnnsRObject$whereAreResults

Get a list of output units of a net
denormalizeData

Revert data normalization
matrixToActMapList

Convert matrix of activations to activation map list
plotRegressionError

Plot a regression error plot
mlp

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

Decode class labels to a binary matrix
setSnnsRSeedValue

DEPRECATED, Set the SnnsR seed value
som

Create and train a self-organizing map (SOM)
outputColumns

Get the columns that are targets
plotActMap

Plot activation map
splitForTrainingAndTest

Function to split data into training and test set
savePatFile

Save data to a pat file
snnsData

Example data of the package
predict.rsnns

Generic predict function for rsnns object
rsnnsObjectFactory

Object factory for generating rsnns objects
train

Internal generic train function for rsnns objects
vectorToActMap

Convert a vector to an activation map
SnnsRObject$createNet

Create a layered network
SnnsRObject$getAllHiddenUnits

Get all hidden units of the net
SnnsRObject$setUnitDefaults

Set the unit defaults
SnnsRObject$getInfoHeader

Get an info header of the network.
RSNNS-package

Getting started with the RSNNS package
SnnsRObject$getAllInputUnits

Get all input units of the net
SnnsRObject$getAllOutputUnits

Get all output units of the net.
SnnsRObject$predictCurrPatSet

Predict values with a trained net
SnnsRObject$initializeNet

Initialize the network
SnnsR-class

The main class of the package
SnnsRObject$getSiteDefinitions

Get the sites definitions of the network.
SnnsRObject$getUnitsByName

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

Get the weight matrix between two sets of units
analyzeClassification

Converts continuous outputs to class labels
art1

Create and train an art1 network