A C D E G I J M N O P R S T V W
RSNNS-package | Getting started with the RSNNS package |
$ | Enable calling of C++ functions as methods of SnnsR-class objects. |
$-method | Enable calling of C++ functions as methods of SnnsR-class objects. |
analyzeClassification | Converts continuous outputs to class labels. |
art1 | Create and train an art1 network. |
art1.default | Create and train an art1 network. |
art2 | Create and train an art2 network. |
art2.default | Create and train an art2 network. |
assoz | Create and train an (auto-)associative memory. |
assoz.default | Create and train an (auto-)associative memory. |
confusionMatrix | Computes a confusion matrix. |
createNet$getAllUnitsTType | Create a layered network. |
createNet-method | Create a layered network. |
createPatSet-method | Create a pattern set. |
decodeClassLabels | Decode class labels from a numerical or levels vector to a binary matrix. |
dlvq | Create and train a dlvq network. |
dlvq.default | Create and train a dlvq network. |
elman | Create and train an elman network. |
elman.default | Create and train an elman network. |
encodeClassLabels | Applies analyzeClassification row-wise to a matrix. |
extractPatterns-method | Extract the current pattern set to a matrix. |
genericPredictCurrPatSet-method | Predict values with a trained net. |
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. |
getAllUnitsTType-method | Get all units in the net of a certain ttype. |
getSnnsRDefine | Get a define of the SNNS kernel. |
getSnnsRFunctionTable | Get the function table of available SNNS functions. |
getUnitsByName-method | Find all units whose name begins with a given prefix. |
initializeNet-method | Initialize the network. |
inputColumns | Function to get the columns that are inputs. |
jordan | Create and train a jordan network. |
jordan.default | Create and train a jordan network. |
matrixToActMapList | Organize a matrix containing 1d vectors of network activations as 2d maps. |
mlp | Create and train a multi-layer perceptron (mlp). |
mlp.default | Create and train a multi-layer perceptron (mlp). |
normalizeData | Data normalization. |
outputColumns | Function to get the columns that are targets. |
plotActMap | Plot an activation map as a heatmap. |
plotIterativeError | Plot the iterative training and test error of the net of this rsnns object. |
plotIterativeError.reg_class | Plot the iterative training and test error of the net of this 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. |
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 a rbf network with the DDA algorithm. |
rbfDDA.default | Create and train a rbf network with the DDA algorithm. |
readPatFile | Load data from a pat file. |
readResFile | Rudimentary parser for res files. |
resetRSNNS-method | Reset the SnnsR-class 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. |
savePatFile | Save data to a pat file. |
setSnnsRSeedValue | Set the seed value used in all SnnsR objects. |
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 | The main class of the package. |
SnnsR-class | The main class of the package. |
SnnsRObject$createPatSet | Create a pattern set. |
SnnsRObject$extractPatterns | Extract the current pattern set to a matrix. |
SnnsRObject$genericPredictCurrPatSet | Predict values with a trained net. |
SnnsRObject$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$getAllUnitsTType | Get all units in the net of a certain ttype. |
SnnsRObject$getUnitsByName | Find all units whose name begins with a given prefix. |
SnnsRObject$initializeNet | Initialize the network. |
SnnsRObject$predictCurrPatSet | Predict values with a trained net. |
SnnsRObject$resetRSNNS | Reset the SnnsR-class object. |
SnnsRObject$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, calculated directly by SNNS. |
SnnsRObject$train | Train a network and test it in every training iteration. |
SnnsRObject$whereAreResults | Get a list of output units of a net. |
SnnsRObjectFactory | Object factory to create a new object of type SnnsR-class. |
SnnsR__createNet | Create a layered network. |
SnnsR__createPatSet | Create a pattern set. |
SnnsR__extractPatterns | Extract the current pattern set to a matrix. |
SnnsR__genericPredictCurrPatSet | Predict values with a trained net. |
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__getAllUnitsTType | Get all units in the net of a certain ttype. |
SnnsR__getUnitsByName | Find all units whose name begins with a given prefix. |
SnnsR__initializeNet | Initialize the network. |
SnnsR__predictCurrPatSet | Predict values with a trained net. |
SnnsR__resetRSNNS | Reset the SnnsR-class 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, calculated directly by SNNS. |
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, calculated directly by SNNS. |
splitForTrainingAndTest | Function to split data into training and test set. |
summary.rsnns | Generic summary function for rsnns objects. |
toNumericClassLabels | Converts a vector (of class labels) to a numeric vector. |
train | Generic train function. |
train-method | Train a network and test it in every training iteration. |
train.rsnns | Generic train function. |
vectorToActMap | Organize network activation as 2d map. |
whereAreResults-method | Get a list of output units of a net. |