# RSNNS v0.4-12

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## Neural Networks using the Stuttgart Neural Network Simulator (SNNS)

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.

## Functions in RSNNS

 Name Description SnnsRObject$createPatSet Create a pattern set SnnsRObjectMethodCaller Method caller for SnnsR objects SnnsRObject$getCompleteWeightMatrix Get the complete weight matrix. elman Create and train an Elman network SnnsRObject$getAllUnitsTType Get all units in the net of a certain ttype. SnnsRObjectFactory SnnsR object factory dlvq Create and train a dlvq network encodeClassLabels Encode a matrix of (decoded) class labels exportToSnnsNetFile Export the net to a file in the original SNNS file format SnnsRObject$resetRSNNS Reset the SnnsR object. SnnsRObject$setTTypeUnitsActFunc Set the activation function for all units of a certain ttype. decodeClassLabels Decode class labels to a binary matrix readResFile Rudimentary parser for res files. train Internal generic train function for rsnns objects print.rsnns Generic print function for rsnns objects getSnnsRDefine Get a define of the SNNS kernel vectorToActMap Convert a vector to an activation map resolveSnnsRDefine Resolve a define of the SNNS kernel denormalizeData Revert data normalization getSnnsRFunctionTable Get SnnsR function table rbf Create and train a radial basis function (RBF) network plotRegressionError Plot a regression error plot artmap Create and train an artmap network SnnsRObject$whereAreResults Get a list of output units of a net mlp Create and train a multi-layer perceptron (MLP) SnnsRObject$predictCurrPatSet Predict values with a trained net art2 Create and train an art2 network SnnsRObject$initializeNet Initialize the network SnnsRObject$train Train a network and test it in every training iteration normTrainingAndTestSet Function to normalize training and test set matrixToActMapList Convert matrix of activations to activation map list normalizeData Data normalization SnnsRObject$getTypeDefinitions Get the FType definitions of the network. SnnsRObject$somPredictCurrPatSetWinners Get most of the relevant results from a som SnnsRObject$somPredictCurrPatSetWinnersSpanTree Get the spanning tree of the SOM SnnsRObject$getUnitDefinitions Get the unit definitions of the network. confusionMatrix Computes a confusion matrix SnnsRObject$getInfoHeader Get an info header of the network. assoz Create and train an (auto-)associative memory som Create and train a self-organizing map (SOM) SnnsRObject$getSiteDefinitions Get the sites definitions of the network. predict.rsnns Generic predict function for rsnns object SnnsRObject$getUnitsByName Find all units whose name begins with a given prefix. SnnsRObject$getWeightMatrix Get the weight matrix between two sets of units setSnnsRSeedValue DEPRECATED, Set the SnnsR seed value SnnsRObject$setUnitDefaults Set the unit defaults SnnsRObject$somPredictComponentMaps Calculate the som component maps snnsData Example data of the package extractNetInfo Extract information from a network art1 Create and train an art1 network analyzeClassification Converts continuous outputs to class labels getNormParameters Get normalization parameters of the input data splitForTrainingAndTest Function to split data into training and test set inputColumns Get the columns that are inputs summary.rsnns Generic summary function for rsnns objects savePatFile Save data to a pat file rsnnsObjectFactory Object factory for generating rsnns objects weightMatrix Function to extract the weight matrix of an rsnns object jordan Create and train a Jordan network plotActMap Plot activation map plotIterativeError Plot iterative errors of an rsnns object outputColumns Get the columns that are targets plotROC Plot a ROC curve rbfDDA Create and train an RBF network with the DDA algorithm readPatFile Load data from a pat file toNumericClassLabels Convert a vector (of class labels) to a numeric vector SnnsRObject$getAllOutputUnits Get all output units of the net. SnnsRObject$getAllUnits Get all units present in the net. RSNNS-package Getting started with the RSNNS package SnnsRObject$getAllInputUnits Get all input units of the net SnnsRObject$createNet Create a layered network SnnsRObject$getAllHiddenUnits Get all hidden units of the net SnnsR-class The main class of the package SnnsRObject$extractNetInfo Get characteristics of the network. SnnsRObject$extractPatterns Extract the current pattern set to a matrix No Results!