SnnsRObject$predictCurrPatSet
Predict values with a trained net.
Create and train an art1 network.
SnnsRObject$getAllOutputUnits
Get all output units of the net.
Create and train an art2 network.
Organize a matrix containing 1d vectors of network activations as 2d maps.
Converts a vector (of class labels) to a numeric vector.
Create a pattern set.
Decode class labels from a numerical or levels vector to a binary matrix.
SnnsRObject$somPredictComponentMaps
Calculate the som component maps.
Train a network and test it in every training iteration.
Applies analyzeClassification row-wise to a matrix.
SnnsRObject$getAllUnitsTType
Get all units in the net of a certain ttype.
SnnsRObject$getAllHiddenUnits
Get all hidden units of the net.
Getting started with the RSNNS package
Function to split data into training and test set.
Create and train an elman network.
Get a define of the SNNS kernel.
Create and train a radial basis function (rbf) network.
Create and train a rbf network with the DDA algorithm.
Create and train a jordan network.
Computes a confusion matrix.
Function to get the columns that are targets.
Create a layered network.
Reset the SnnsR-class object.
Plot a regression error plot.
Generic train function.
Organize network activation as 2d map.
Set the seed value used in all SnnsR objects.
Create and train a multi-layer perceptron (mlp).
SnnsRObject$getAllInputUnits
Get all input units of the net.
SnnsRObject$setTTypeUnitsActFunc
Set the activation function for all units of a certain ttype.
Generic summary function for rsnns objects.
Plot an activation map as a heatmap.
Create and train an (auto-)associative memory.
Save data to a pat file.
Resolve a define of the SNNS kernel.
Load data from a pat file.
Object factory for generating rsnns objects.
SnnsRObject$somPredictCurrPatSetWinnersSpanTree
Get the spanning tree of the som, calculated directly by SNNS.
Converts continuous outputs to class labels.
The main class of the package.
SnnsRObject$extractPatterns
Extract the current pattern set to a matrix.
SnnsRObject$somPredictCurrPatSetWinners
Get most of the relevant results from a som.
Object factory to create a new object of type SnnsR-class.
Generic predict function for rsnns object.
Enable calling of C++ functions as methods of SnnsR-class objects.
SnnsRObject$initializeNet
Initialize the network.
SnnsRObject$setUnitDefaults
Set the unit defaults.
Create and train a dlvq network.
Function to get the columns that are inputs.
Data normalization.
Plot the iterative training and test error of the net of this rsnns object.
Example data of the package.
Plot a ROC curve.
Rudimentary parser for res files.
SnnsRObject$genericPredictCurrPatSet
Predict values with a trained net.
SnnsRObject$getUnitsByName
Find all units whose name begins with a given prefix.
Get the function table of available SNNS functions.
Generic print function for rsnns objects.
Create and train a self-organizing map (som).
SnnsRObject$whereAreResults
Get a list of output units of a net.