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