RSNNS: Neural Networks in R 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.

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
https://github.com/cbergmeir/RSNNS

View on CRAN

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

Files in this package

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

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