RSNNS-package           Getting started with the RSNNS 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
analyzeClassification   Converts continuous outputs to class labels
art1                    Create and train an art1 network
art2                    Create and train an art2 network
artmap                  Create and train an artmap network
assoz                   Create and train an (auto-)associative memory
confusionMatrix         Computes a confusion matrix
decodeClassLabels       Decode class labels to a binary matrix
denormalizeData         Revert data normalization
dlvq                    Create and train a dlvq network
elman                   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
getNormParameters       Get normalization parameters of the input data
getSnnsRDefine          Get a define of the SNNS kernel
getSnnsRFunctionTable   Get SnnsR function table
inputColumns            Get the columns that are inputs
jordan                  Create and train a Jordan network
matrixToActMapList      Convert matrix of activations to activation map
                        list
mlp                     Create and train a multi-layer perceptron (MLP)
normTrainingAndTestSet
                        Function to normalize training and test set
normalizeData           Data normalization
outputColumns           Get the columns that are targets
plotActMap              Plot activation map
plotIterativeError      Plot iterative errors of an rsnns object
plotROC                 Plot a ROC curve
plotRegressionError     Plot a regression error plot
predict.rsnns           Generic predict function for rsnns object
print.rsnns             Generic print function for rsnns objects
rbf                     Create and train a radial basis function (RBF)
                        network
rbfDDA                  Create and train an RBF network with the DDA
                        algorithm
readPatFile             Load data from a pat file
readResFile             Rudimentary parser for res files.
resolveSnnsRDefine      Resolve a define of the SNNS kernel
rsnnsObjectFactory      Object factory for generating rsnns objects
savePatFile             Save data to a pat file
setSnnsRSeedValue       DEPRECATED, Set the SnnsR seed value
snnsData                Example data of the package
som                     Create and train a self-organizing map (SOM)
splitForTrainingAndTest
                        Function to split data into training and test
                        set
summary.rsnns           Generic summary function for rsnns objects
toNumericClassLabels    Convert a vector (of class labels) to a numeric
                        vector
train                   Internal generic train function for rsnns
                        objects
vectorToActMap          Convert a vector to an activation map
weightMatrix            Function to extract the weight matrix of an
                        rsnns object
