Man pages for RSNNS
Neural Networks using the Stuttgart Neural Network Simulator (SNNS)
| analyzeClassification | Converts continuous outputs to class labels |
| art1 | Create and train an art1 network |
| art2 | Create and train an art2 network |
| artmap | Create and train an artmap network |
| assoz | Create and train an (auto-)associative memory |
| confusionMatrix | Computes a confusion matrix |
| decodeClassLabels | Decode class labels to a binary matrix |
| denormalizeData | Revert data normalization |
| dlvq | Create and train a dlvq network |
| elman | Create and train an Elman network |
| encodeClassLabels | Encode a matrix of (decoded) class labels |
| exportToSnnsNetFile | Export the net to a file in the original SNNS file format |
| extractNetInfo | Extract information from a network |
| getNormParameters | Get normalization parameters of the input data |
| getSnnsRDefine | Get a define of the SNNS kernel |
| getSnnsRFunctionTable | Get SnnsR function table |
| inputColumns | Get the columns that are inputs |
| jordan | Create and train a Jordan network |
| matrixToActMapList | Convert matrix of activations to activation map list |
| mlp | Create and train a multi-layer perceptron (MLP) |
| normalizeData | Data normalization |
| normTrainingAndTestSet | Function to normalize training and test set |
| outputColumns | Get the columns that are targets |
| plotActMap | Plot activation map |
| plotIterativeError | Plot iterative errors of an rsnns object |
| plotRegressionError | Plot a regression error plot |
| plotROC | Plot a ROC curve |
| predict.rsnns | Generic predict function for rsnns object |
| print.rsnns | Generic print function for rsnns objects |
| rbf | Create and train a radial basis function (RBF) network |
| rbfDDA | Create and train an RBF network with the DDA algorithm |
| readPatFile | Load data from a pat file |
| readResFile | Rudimentary parser for res files. |
| resolveSnnsRDefine | Resolve a define of the SNNS kernel |
| rsnnsObjectFactory | Object factory for generating rsnns objects |
| RSNNS-package | Getting started with the RSNNS package |
| savePatFile | Save data to a pat file |
| setSnnsRSeedValue | DEPRECATED, Set the SnnsR seed value |
| snnsData | Example data of the package |
| SnnsR-class | The main class of the package |
| SnnsRObject-createNet | Create a layered network |
| SnnsRObject-createPatSet | Create a pattern set |
| SnnsRObject-extractNetInfo | Get characteristics of the network. |
| SnnsRObject-extractPatterns | Extract the current pattern set to a matrix |
| SnnsRObjectFactory | SnnsR object factory |
| 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-getAllUnits | Get all units present in the net. |
| SnnsRObject-getAllUnitsTType | Get all units in the net of a certain 'ttype'. |
| SnnsRObject-getCompleteWeightMatrix | Get the complete weight matrix. |
| SnnsRObject-getInfoHeader | Get an info header of the network. |
| SnnsRObject-getSiteDefinitions | Get the sites definitions of the network. |
| SnnsRObject-getTypeDefinitions | Get the FType definitions of the network. |
| SnnsRObject-getUnitDefinitions | Get the unit definitions of the network. |
| SnnsRObject-getUnitsByName | Find all units whose name begins with a given prefix. |
| SnnsRObject-getWeightMatrix | Get the weight matrix between two sets of units |
| SnnsRObject-initializeNet | Initialize the network |
| SnnsRObjectMethodCaller | Method caller for SnnsR objects |
| SnnsRObject-predictCurrPatSet | Predict values with a trained net |
| SnnsRObject-resetRSNNS | Reset the SnnsR 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 |
| SnnsRObject-train | Train a network and test it in every training iteration |
| SnnsRObject-whereAreResults | Get a list of output units of a net |
| som | Create and train a self-organizing map (SOM) |
| splitForTrainingAndTest | Function to split data into training and test set |
| summary.rsnns | Generic summary function for rsnns objects |
| toNumericClassLabels | Convert a vector (of class labels) to a numeric vector |
| train | Internal generic train function for rsnns objects |
| vectorToActMap | Convert a vector to an activation map |
| weightMatrix | Function to extract the weight matrix of an rsnns object |
