Neural Networks using the Stuttgart Neural Network Simulator (SNNS)

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Documentation for package ‘RSNNS’ version 0.4-17

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A C D E G I J M N O P R S T V W misc

RSNNS-package Getting started with the RSNNS package

-- A --

analyzeClassification Converts continuous outputs to class labels
art1 Create and train an art1 network
art1.default Create and train an art1 network
art2 Create and train an art2 network
art2.default Create and train an art2 network
artmap Create and train an artmap network
artmap.default Create and train an artmap network
assoz Create and train an (auto-)associative memory
assoz.default Create and train an (auto-)associative memory

-- C --

confusionMatrix Computes a confusion matrix
createNet-method Create a layered network
createPatSet-method Create a pattern set

-- D --

decodeClassLabels Decode class labels to a binary matrix
denormalizeData Revert data normalization
dlvq Create and train a dlvq network
dlvq.default Create and train a dlvq network

-- E --

elman Create and train an Elman network
elman.default Create and train an Elman network
encodeClassLabels Encode a matrix of (decoded) class labels
exportToSnnsNetFile Export the net to a file in the original SNNS file format
extractNetInfo Extract information from a network
extractNetInfo-method Get characteristics of the network.
extractPatterns-method Extract the current pattern set to a matrix

-- G --

getAllHiddenUnits-method Get all hidden units of the net
getAllInputUnits-method Get all input units of the net
getAllOutputUnits-method Get all output units of the net.
getAllUnits-method Get all units present in the net.
getAllUnitsTType-method Get all units in the net of a certain 'ttype'.
getCompleteWeightMatrix-method Get the complete weight matrix.
getInfoHeader-method Get an info header of the network.
getNormParameters Get normalization parameters of the input data
getSiteDefinitions-method Get the sites definitions of the network.
getSnnsRDefine Get a define of the SNNS kernel
getSnnsRFunctionTable Get SnnsR function table
getTypeDefinitions-method Get the FType definitions of the network.
getUnitDefinitions-method Get the unit definitions of the network.
getUnitsByName-method Find all units whose name begins with a given prefix.
getWeightMatrix-method Get the weight matrix between two sets of units

-- I --

initializeNet-method Initialize the network
inputColumns Get the columns that are inputs

-- J --

jordan Create and train a Jordan network
jordan.default Create and train a Jordan network

-- M --

matrixToActMapList Convert matrix of activations to activation map list
mlp Create and train a multi-layer perceptron (MLP)
mlp.default Create and train a multi-layer perceptron (MLP)

-- N --

normalizeData Data normalization
normTrainingAndTestSet Function to normalize training and test set

-- O --

outputColumns Get the columns that are targets

-- P --

plotActMap Plot activation map
plotIterativeError Plot iterative errors of an rsnns object
plotIterativeError.rsnns Plot iterative errors of an rsnns object
plotRegressionError Plot a regression error plot
plotROC Plot a ROC curve
predict.rsnns Generic predict function for rsnns object
predictCurrPatSet-method Predict values with a trained net
print.rsnns Generic print function for rsnns objects

-- R --

rbf Create and train a radial basis function (RBF) network
rbf.default Create and train a radial basis function (RBF) network
rbfDDA Create and train an RBF network with the DDA algorithm
rbfDDA.default Create and train an RBF network with the DDA algorithm
readPatFile Load data from a pat file
readResFile Rudimentary parser for res files.
resetRSNNS-method Reset the SnnsR object.
resolveSnnsRDefine Resolve a define of the SNNS kernel
RSNNS Getting started with the RSNNS package
rsnns Object factory for generating rsnns objects
rsnnsObjectFactory Object factory for generating rsnns objects

-- S --

savePatFile Save data to a pat file
setSnnsRSeedValue DEPRECATED, Set the SnnsR seed value
setTTypeUnitsActFunc-method Set the activation function for all units of a certain ttype.
setUnitDefaults-method Set the unit defaults
snnsData Example data of the package
SnnsR-class The main class of the package
SnnsRObject$createNet Create a layered network
SnnsRObject$createPatSet Create a pattern set
SnnsRObject$extractNetInfo Get characteristics of the network.
SnnsRObject$extractPatterns Extract the current pattern set to a matrix
SnnsRObject$getAllHiddenUnits Get all hidden units of the net
SnnsRObject$getAllInputUnits Get all input units of the net
SnnsRObject$getAllOutputUnits Get all output units of the net.
SnnsRObject$getAllUnits Get all units present in the net.
SnnsRObject$getAllUnitsTType Get all units in the net of a certain 'ttype'.
SnnsRObject$getCompleteWeightMatrix Get the complete weight matrix.
SnnsRObject$getInfoHeader Get an info header of the network.
SnnsRObject$getSiteDefinitions Get the sites definitions of the network.
SnnsRObject$getTypeDefinitions Get the FType definitions of the network.
SnnsRObject$getUnitDefinitions Get the unit 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
SnnsRObject$initializeNet Initialize the network
SnnsRObject$predictCurrPatSet Predict values with a trained net
SnnsRObject$resetRSNNS Reset the SnnsR object.
SnnsRObject$setTTypeUnitsActFunc Set the activation function for all units of a certain ttype.
SnnsRObject$setUnitDefaults Set the unit defaults
SnnsRObject$somPredictComponentMaps Calculate the som component maps
SnnsRObject$somPredictCurrPatSetWinners Get most of the relevant results from a som
SnnsRObject$somPredictCurrPatSetWinnersSpanTree Get the spanning tree of the SOM
SnnsRObject$train Train a network and test it in every training iteration
SnnsRObject$whereAreResults Get a list of output units of a net
SnnsRObjectFactory SnnsR object factory
SnnsRObjectMethodCaller Method caller for SnnsR objects
SnnsR__createNet Create a layered network
SnnsR__createPatSet Create a pattern set
SnnsR__extractNetInfo Get characteristics of the network.
SnnsR__extractPatterns Extract the current pattern set to a matrix
SnnsR__getAllHiddenUnits Get all hidden units of the net
SnnsR__getAllInputUnits Get all input units of the net
SnnsR__getAllOutputUnits Get all output units of the net.
SnnsR__getAllUnits Get all units present in the net.
SnnsR__getAllUnitsTType Get all units in the net of a certain 'ttype'.
SnnsR__getCompleteWeightMatrix Get the complete weight matrix.
SnnsR__getInfoHeader Get an info header of the network.
SnnsR__getSiteDefinitions Get the sites definitions of the network.
SnnsR__getTypeDefinitions Get the FType definitions of the network.
SnnsR__getUnitDefinitions Get the unit definitions of the network.
SnnsR__getUnitsByName Find all units whose name begins with a given prefix.
SnnsR__getWeightMatrix Get the weight matrix between two sets of units
SnnsR__initializeNet Initialize the network
SnnsR__predictCurrPatSet Predict values with a trained net
SnnsR__resetRSNNS Reset the SnnsR object.
SnnsR__setTTypeUnitsActFunc Set the activation function for all units of a certain ttype.
SnnsR__setUnitDefaults Set the unit defaults
SnnsR__somPredictComponentMaps Calculate the som component maps
SnnsR__somPredictCurrPatSetWinners Get most of the relevant results from a som
SnnsR__somPredictCurrPatSetWinnersSpanTree Get the spanning tree of the SOM
SnnsR__train Train a network and test it in every training iteration
SnnsR__whereAreResults Get a list of output units of a net
som Create and train a self-organizing map (SOM)
som.default Create and train a self-organizing map (SOM)
somPredictComponentMaps-method Calculate the som component maps
somPredictCurrPatSetWinners-method Get most of the relevant results from a som
somPredictCurrPatSetWinnersSpanTree-method Get the spanning tree of the SOM
splitForTrainingAndTest Function to split data into training and test set
summary.rsnns Generic summary function for rsnns objects

-- T --

toNumericClassLabels Convert a vector (of class labels) to a numeric vector
train Internal generic train function for rsnns objects
train-method Train a network and test it in every training iteration
train.rsnns Internal generic train function for rsnns objects

-- V --

vectorToActMap Convert a vector to an activation map

-- W --

weightMatrix Function to extract the weight matrix of an rsnns object
weightMatrix.rsnns Function to extract the weight matrix of an rsnns object
whereAreResults-method Get a list of output units of a net

-- misc --

$ Method caller for SnnsR objects
$-method Method caller for SnnsR objects