Create and train an Elman network
Encode a matrix of (decoded) class labels
Create and train a dlvq network
Create and train an art2 network
Revert data normalization
Create and train an (auto-)associative memory
Create and train an artmap network
Create and train an art1 network
Computes a confusion matrix
Decode class labels to a binary matrix
Get the columns that are inputs
Get SnnsR function table
Create and train a Jordan network
Create and train a multi-layer perceptron (MLP)
Convert matrix of activations to activation map list
Extract information from a network
Export the net to a file in the original SNNS file format
Function to normalize training and test set
Get a define of the SNNS kernel
Get normalization parameters of the input data
Plot a regression error plot
Plot iterative errors of an rsnns object
Rudimentary parser for res files.
Plot a ROC curve
Resolve a define of the SNNS kernel
Object factory for generating rsnns objects
Getting started with the RSNNS package
Generic predict function for rsnns object
Get the columns that are targets
Plot activation map
Example data of the package
Create a layered network
SnnsRObject$getCompleteWeightMatrix
Get the complete weight matrix.
Generic print function for rsnns objects
Reset the SnnsR object.
SnnsRObject$getInfoHeader
Get an info header of the network.
SnnsRObject$predictCurrPatSet
Predict values with a trained net
Save data to a pat file
Create and train a radial basis function (RBF) network
DEPRECATED, Set the SnnsR seed value
SnnsRObject$getSiteDefinitions
Get the sites definitions of the network.
SnnsRObject$getTypeDefinitions
Get the FType definitions of the network.
SnnsRObject$getWeightMatrix
Get the weight matrix between two sets of units
SnnsRObject$getUnitDefinitions
Get the unit definitions of the network.
SnnsRObject$getAllUnitsTType
Get all units in the net of a certain ttype
.
Get all units present in the net.
SnnsRObject$initializeNet
Initialize the network
Function to split data into training and test set
SnnsRObject$getUnitsByName
Find all units whose name begins with a given prefix.
Generic summary function for rsnns objects
Create and train a self-organizing map (SOM)
Method caller for SnnsR objects
SnnsRObject$extractPatterns
Extract the current pattern set to a matrix
Convert a vector (of class labels) to a numeric vector
SnnsRObject$setUnitDefaults
Set the unit defaults
SnnsRObject$setTTypeUnitsActFunc
Set the activation function for all units of a certain ttype.
SnnsRObject$getAllHiddenUnits
Get all hidden units of the net
Create and train an RBF network with the DDA algorithm
Internal generic train function for rsnns objects
Load data from a pat file
Create a pattern set
SnnsRObject$extractNetInfo
Get characteristics of the network.
SnnsRObject$somPredictComponentMaps
Calculate the som component maps
SnnsRObject$somPredictCurrPatSetWinners
Get most of the relevant results from a som
Convert a vector to an activation map
SnnsR object factory
SnnsRObject$whereAreResults
Get a list of output units of a net
SnnsRObject$getAllInputUnits
Get all input units of the net
Function to extract the weight matrix of an rsnns object
SnnsRObject$getAllOutputUnits
Get all output units of the net.
Train a network and test it in every training iteration
SnnsRObject$somPredictCurrPatSetWinnersSpanTree
Get the spanning tree of the SOM