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