RSNNS: Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS)
Version 0.4-9

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.

AuthorChristoph Bergmeir and José M. Benítez
Date of publication2016-12-16 08:33:39
MaintainerChristoph Bergmeir <c.bergmeir@decsai.ugr.es>
LicenseLGPL (>= 2) | file LICENSE
Version0.4-9
URL https://github.com/cbergmeir/RSNNS
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("RSNNS")

Getting started

Package overview

Popular man pages

elman: Create and train an Elman network
jordan: Create and train a Jordan network
mlp: Create and train a multi-layer perceptron (MLP)
predict.rsnns: Generic predict function for rsnns object
rbfDDA: Create and train an RBF network with the DDA algorithm
snnsData: Example data of the package
splitForTrainingAndTest: Function to split data into training and test set
See all...

All man pages Function index File listing

Man pages

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)
normalizeData: Data normalization
normTrainingAndTestSet: Function to normalize training and test set
outputColumns: Get the columns that are targets
plotActMap: Plot activation map
plotIterativeError: 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
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
RSNNS-package: Getting started with the RSNNS package
savePatFile: Save data to a pat file
setSnnsRSeedValue: DEPRECATED, Set the SnnsR seed value
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
SnnsRObjectFactory: SnnsR object factory
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
SnnsRObjectMethodCaller: Method caller for SnnsR objects
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
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

Functions

$ Man page
$,SnnsR-method Man page
RSNNS Man page
RSNNS-package Man page
SnnsR-class Man page
SnnsRObject$createNet Man page
SnnsRObject$createPatSet Man page
SnnsRObject$extractNetInfo Man page
SnnsRObject$extractPatterns Man page
SnnsRObject$getAllHiddenUnits Man page
SnnsRObject$getAllInputUnits Man page
SnnsRObject$getAllOutputUnits Man page
SnnsRObject$getAllUnits Man page
SnnsRObject$getAllUnitsTType Man page
SnnsRObject$getCompleteWeightMatrix Man page
SnnsRObject$getInfoHeader Man page
SnnsRObject$getSiteDefinitions Man page
SnnsRObject$getTypeDefinitions Man page
SnnsRObject$getUnitDefinitions Man page
SnnsRObject$getUnitsByName Man page
SnnsRObject$getWeightMatrix Man page
SnnsRObject$initializeNet Man page
SnnsRObject$predictCurrPatSet Man page
SnnsRObject$resetRSNNS Man page
SnnsRObject$setTTypeUnitsActFunc Man page
SnnsRObject$setUnitDefaults Man page
SnnsRObject$somPredictComponentMaps Man page
SnnsRObject$somPredictCurrPatSetWinners Man page
SnnsRObject$somPredictCurrPatSetWinnersSpanTree Man page
SnnsRObject$train Man page
SnnsRObject$whereAreResults Man page
SnnsRObjectFactory Man page Source code
SnnsRObjectMethodCaller Man page
SnnsR__createNet Man page Source code
SnnsR__createPatSet Man page Source code
SnnsR__deserialize Source code
SnnsR__extractNetInfo Man page Source code
SnnsR__extractPatterns Man page Source code
SnnsR__getAllHiddenUnits Man page Source code
SnnsR__getAllInputUnits Man page Source code
SnnsR__getAllOutputUnits Man page Source code
SnnsR__getAllUnits Man page Source code
SnnsR__getAllUnitsTType Man page Source code
SnnsR__getCompleteWeightMatrix Man page Source code
SnnsR__getConnectionDefs Source code
SnnsR__getInfoHeader Man page Source code
SnnsR__getLayerDefs Source code
SnnsR__getSiteDefinitions Man page Source code
SnnsR__getSubnetDefs Source code
SnnsR__getTimeDelayDefs Source code
SnnsR__getTypeDefinitions Man page Source code
SnnsR__getUnitDefinitions Man page Source code
SnnsR__getUnitsByName Man page Source code
SnnsR__getWeightMatrix Man page Source code
SnnsR__initializeNet Man page Source code
SnnsR__predictCurrPatSet Man page Source code
SnnsR__resetRSNNS Man page Source code
SnnsR__setTTypeUnitsActFunc Man page Source code
SnnsR__setUnitDefaults Man page Source code
SnnsR__somPredictComponentMaps Man page Source code
SnnsR__somPredictCurrPatSetWinners Man page Source code
SnnsR__somPredictCurrPatSetWinnersSpanTree Man page Source code
SnnsR__train Man page Source code
SnnsR__whereAreResults Man page Source code
analyzeClassification Man page Source code
art1 Man page Source code
art1.default Man page Source code
art2 Man page Source code
art2.default Man page Source code
artmap Man page Source code
artmap.default Man page Source code
assoz Man page Source code
assoz.default Man page Source code
beginsWith Source code
checkInput Source code
computeNormalizationParameters Source code
confusionMatrix Man page Source code
createNet,SnnsR-method Man page
createPatSet,SnnsR-method Man page
decodeClassLabels Man page Source code
denormalizeData Man page Source code
dlvq Man page Source code
dlvq.default Man page Source code
elman Man page Source code
elman.default Man page Source code
encodeClassLabels Man page Source code
endsWith Source code
exportToSnnsNetFile Man page Source code
extractNetInfo Man page Source code
extractNetInfo,SnnsR-method Man page
extractPatterns,SnnsR-method Man page
getAllHiddenUnits,SnnsR-method Man page
getAllInputUnits,SnnsR-method Man page
getAllOutputUnits,SnnsR-method Man page
getAllUnits,SnnsR-method Man page
getAllUnitsTType,SnnsR-method Man page
getCompleteWeightMatrix,SnnsR-method Man page
getInfoHeader,SnnsR-method Man page
getKrioTitle Source code
getNormParameters Man page Source code
getSiteDefinitions,SnnsR-method Man page
getSnnsRDefine Man page Source code
getSnnsRFunctionTable Man page Source code
getTypeDefinitions,SnnsR-method Man page
getUnitDefinitions,SnnsR-method Man page
getUnitsByName,SnnsR-method Man page
getWeightMatrix,SnnsR-method Man page
initializeNet,SnnsR-method Man page
inputColumns Man page Source code
is.nil Source code
jordan Man page Source code
jordan.default Man page Source code
matrixToActMapList Man page Source code
mlp Man page Source code
mlp.default Man page Source code
normTrainingAndTestSet Man page Source code
normalizeData Man page Source code
normalizeDataWithParams Source code
outputColumns Man page Source code
plotActMap Man page Source code
plotIterativeError Man page Source code
plotIterativeError.rsnns Man page Source code
plotROC Man page Source code
plotRegressionError Man page Source code
predict.rsnns Man page Source code
predictCurrPatSet,SnnsR-method Man page
print.rsnns Man page Source code
rbf Man page Source code
rbf.default Man page Source code
rbfDDA Man page Source code
rbfDDA.default Man page Source code
readPatFile Man page Source code
readResFile Man page Source code
resetRSNNS,SnnsR-method Man page
resolveSnnsRDefine Man page Source code
rot90 Source code
rsnns Man page
rsnnsObjectFactory Man page Source code
savePatFile Man page Source code
setSnnsRSeedValue Man page Source code
setTTypeUnitsActFunc,SnnsR-method Man page
setUnitDefaults,SnnsR-method Man page
snnsData Man page
som Man page Source code
som.default Man page Source code
somPredictComponentMaps,SnnsR-method Man page
somPredictCurrPatSetWinners,SnnsR-method Man page
somPredictCurrPatSetWinnersSpanTree,SnnsR-method Man page
splitForTrainingAndTest Man page Source code
summary.rsnns Man page Source code
toNumericClassLabels Man page Source code
train Man page Source code
train,SnnsR-method Man page
train.rsnns Man page Source code
vectorToActMap Man page Source code
weightMatrix Man page Source code
weightMatrix.rsnns Man page Source code
whereAreResults,SnnsR-method Man page

Files

inst
inst/CITATION
inst/doc
inst/doc/KnownIssues
tests
tests/testAllDemos.R
src
src/update_f.cpp
src/SnnsCLib.cpp
src/prun_f.h
src/ext_typ.h
src/SnnsCLibWrapper.cpp
src/cc_modify.h
src/Makevars
src/sigmoid_tbl.h
src/func_mac.h
src/kr_art.cpp
src/cc_mac.h
src/u_lrand48.h
src/cc_type.h
src/stochastic_learn_f.h
src/func_tbl.cpp
src/cc_modify.cpp
src/bn_art2.h
src/bn_artmap.cpp
src/krart_df.h
src/kr_td.h
src/tacoma_learn.cpp
src/arttr_f.cpp
src/bn_kohonen.cpp
src/cc_display.cpp
src/SnnsCLib.h
src/version.h
src/kr_mac.h
src/kr_const.h
src/krui_typ.h
src/kr_inversion.cpp
src/kr_art.h
src/scaled_conj_grad.h
src/cc_display.h
src/art_ui.h
src/kr_newpattern.h
src/kr_pat_parse.cpp
src/arttr_f.h
src/trans_f.h
src/kr_amap.cpp
src/dlvq_learn.cpp
src/scaled_conj_grad.cpp
src/bn_art1.cpp
src/kr_funcs.cpp
src/kr_ui.cpp
src/dlvq_type.h
src/matrix.cpp
src/tacoma_learn.h
src/bn_JordElm.h
src/tbl_func.cpp
src/u_lrand48.cpp
src/bn_kohonen.h
src/SnnsCLibGenericR_util.c
src/kr_JordElm.h
src/kr_inversion.h
src/learn_f.cpp
src/tbl_func.h
src/bn_art2.cpp
src/stochastic_learn_f.cpp
src/kr_io.cpp
src/remap_f.h
src/trans_f.cpp
src/kr_def.h
src/kr_typ.h
src/art_typ.h
src/bn_art1.h
src/init_f.h
src/kr_pat_parse.h
src/kr_td.cpp
src/kr_art1.cpp
src/init_f.cpp
src/kr_mem.cpp
src/cc_glob.h
src/func_tbl.h
src/cc_learn.cpp
src/kr_art2.h
src/glob_typ.h
src/cc_glob.cpp
src/learn_f.h
src/kernel.h
src/bn_assoz.cpp
src/bn_JordElm.cpp
src/bn_artmap.h
src/kr_ui.h
src/kernel.cpp
src/dlvq_learn.h
src/kr_pat_scan.cpp
src/kr_pat_scan.h
src/cc_learn.h
src/kr_mem.h
src/art_ui.cpp
src/y.tab.h
src/kr_JordElm.cpp
src/kr_newpattern.cpp
src/prun_f.cpp
src/Makevars.win
src/kr_art2.cpp
src/kr_funcs.h
src/cc_prune.h
src/remap_f.cpp
src/cc_prune.cpp
src/SnnsCLibGeneric_util.h
src/kr_io.h
src/bn_assoz.h
src/kr_amap.h
src/enzo_mem_typ.h
src/kr_art1.h
src/update_f.h
src/matrix.h
NAMESPACE
demo
demo/art2_tetraSnnsR.R
demo/mlp_1dim_eval.R
demo/encoderSnnsCLib.R
demo/assoz_lettersSnnsR.R
demo/art1_lettersSnnsR.R
demo/iris.R
demo/mlp_complex_plot.R
demo/rbfDDA_spiralsSnnsR.R
demo/mlp_iris_tuning.R
demo/eight_elmanSnnsR.R
demo/mlp_irisSnnsR.R
demo/mlp_my_predict.R
demo/rbf_irisSnnsR.R
demo/artmap_lettersSnnsR.R
demo/mlp_plot_with_my_predict.R
demo/laser.R
demo/rbf_sinSnnsR.R
demo/assoz_letters.R
demo/som_iris.R
demo/mlp_binary_eval.R
demo/art2_tetra.R
demo/pruning_iris.R
demo/som_cubeSnnsR.R
demo/pruning_irisSnnsR.R
demo/mlp_complex_eval.R
demo/mlp_plot.R
demo/00Index
demo/mlp_eval6.R
demo/art1_letters.R
demo/mlp_eval.R
demo/dlvq_ziffSnnsR.R
demo/artmap_letters.R
demo/rbf_sin.R
demo/eight_elman.R
demo/dlvq_ziff.R
data
data/snnsData.RData
R
R/SnnsR_masked.R
R/SnnsR_train.R
R/elman.R
R/assoz.R
R/rbf.R
R/rbfDDA.R
R/rsnns.R
R/SnnsRObjectFactory.R
R/SnnsR_util.R
R/normalizeData.R
R/SnnsR_patterns.R
R/mlp.R
R/reg_class.R
R/SnnsR_extractNetInfo.R
R/SnnsR_parser.R
R/SnnsR_createNets.R
R/art1.R
R/docData.R
R/som.R
R/RSNNS-package.R
R/util.R
R/artmap.R
R/dlvq.R
R/art2.R
R/jordan.R
R/parser.R
R/SnnsDefines.R
MD5
DESCRIPTION
ChangeLog
man
man/exportToSnnsNetFile.Rd
man/SnnsRObject-getUnitDefinitions.Rd
man/jordan.Rd
man/matrixToActMapList.Rd
man/SnnsRObject-extractPatterns.Rd
man/splitForTrainingAndTest.Rd
man/SnnsRObject-extractNetInfo.Rd
man/getSnnsRDefine.Rd
man/SnnsRObject-getInfoHeader.Rd
man/SnnsR-class.Rd
man/SnnsRObject-getAllOutputUnits.Rd
man/encodeClassLabels.Rd
man/SnnsRObject-whereAreResults.Rd
man/rbf.Rd
man/normTrainingAndTestSet.Rd
man/SnnsRObject-getSiteDefinitions.Rd
man/SnnsRObject-somPredictCurrPatSetWinnersSpanTree.Rd
man/rsnnsObjectFactory.Rd
man/predict.rsnns.Rd
man/SnnsRObject-initializeNet.Rd
man/plotRegressionError.Rd
man/SnnsRObject-train.Rd
man/toNumericClassLabels.Rd
man/outputColumns.Rd
man/analyzeClassification.Rd
man/SnnsRObject-predictCurrPatSet.Rd
man/SnnsRObject-createPatSet.Rd
man/SnnsRObject-getCompleteWeightMatrix.Rd
man/SnnsRObjectFactory.Rd
man/savePatFile.Rd
man/inputColumns.Rd
man/assoz.Rd
man/print.rsnns.Rd
man/RSNNS-package.Rd
man/train.Rd
man/rbfDDA.Rd
man/som.Rd
man/elman.Rd
man/vectorToActMap.Rd
man/SnnsRObject-createNet.Rd
man/plotROC.Rd
man/readPatFile.Rd
man/SnnsRObject-somPredictComponentMaps.Rd
man/getNormParameters.Rd
man/resolveSnnsRDefine.Rd
man/SnnsRObject-setTTypeUnitsActFunc.Rd
man/getSnnsRFunctionTable.Rd
man/weightMatrix.Rd
man/decodeClassLabels.Rd
man/confusionMatrix.Rd
man/normalizeData.Rd
man/readResFile.Rd
man/SnnsRObjectMethodCaller.Rd
man/SnnsRObject-getAllInputUnits.Rd
man/denormalizeData.Rd
man/SnnsRObject-somPredictCurrPatSetWinners.Rd
man/plotActMap.Rd
man/SnnsRObject-getAllHiddenUnits.Rd
man/extractNetInfo.Rd
man/art2.Rd
man/summary.rsnns.Rd
man/SnnsRObject-getTypeDefinitions.Rd
man/SnnsRObject-getAllUnitsTType.Rd
man/SnnsRObject-getUnitsByName.Rd
man/SnnsRObject-getWeightMatrix.Rd
man/artmap.Rd
man/art1.Rd
man/plotIterativeError.Rd
man/dlvq.Rd
man/SnnsRObject-getAllUnits.Rd
man/snnsData.Rd
man/SnnsRObject-resetRSNNS.Rd
man/mlp.Rd
man/setSnnsRSeedValue.Rd
man/SnnsRObject-setUnitDefaults.Rd
LICENSE
RSNNS documentation built on May 19, 2017, 10:13 p.m.

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