DArch                   Class for deep architectures
Net                     Abtract class for neural networks.
RBM                     Class for Restricted-Bolzmann-Machine
addExecOutput           Adds an execution output for a DArch object
addLayer                Adds a layer to the DArch object
addLayerField           Adds a field to a layer
backpropagation         Backpropagation learning function
binSigmoidUnit          Binary sigmoid unit function.
crossEntropyError       Cross entropy error function
darch                   Deep architectures in R
fineTuneDArch           Fine tuning function for the deep architecture.
generateRBMs            Generates the rbm's for the pre-training.
generateWeights         Generates a weight matrix.
getBatchSize            Returns the batch size of the 'Net'.
getCancel               Returns the cancel value.
getCancelMessage        Returns the cancel message.
getErrorFunction        Returns the error function of the 'Net'.
getExecOutput           Returns the execution output of the layer from
                        the 'DArch' object
getExecOutputs          Returns the execution output list of the
                        'DArch' object
getExecuteFunction      Returns the function for the execution of the
                        'DArch' network.
getFF                   Returns if the weights are saved as ff objects
getFinalMomentum        Returns the final momentum of the 'Net'.
getFineTuneFunction     Returns the fine tune function for the 'DArch'
                        object.
getGenWeightFunction    Returns the function for generating weight
                        matrices.
getHiddenBiases         Returns the biases of the hidden units.
getHiddenBiasesInc      Returns the update value for the biases of the
                        hidden units.
getHiddenUnitStates     Returns a list with the states of the hidden
                        units.
getLayer                Returns a layer from the 'DArch' object.
getLayerField           Returns the field of a layer from the 'DArch'
                        object.
getLayerFunction        Returns the neuron function of a layer from the
                        'DArch' object.
getLayerWeights         Returns the weights of a layer from the 'DArch'
                        object.
getLayers               Returns the a list of layers from the 'DArch'
                        object.
getLearnRateBiasHidden
                        Returns the learning rate for the hidden
                        biases.
getLearnRateBiasVisible
                        Returns the learning rate for the visible
                        biases.
getLearnRateBiases      Returns the learning rate for the bias weigths
                        of the 'DArch' object.
getLearnRateWeights     Returns the learn rate of the weights.
getMomentum             Returns the momentum of the 'Net'.
getMomentumSwitch       Returns the momentum switch of the 'Net'.
getNumHidden            Returns the number of hidden units of the 'RBM'
getNumVisible           Returns the number of visible units of the
                        'RBM'
getOutput               Returns the output of the 'RBM'
getPosPhaseData         Returns the data for the positive phaes.
getRBMList              Returns a list of 'RBM's of the 'DArch' object.
getStats                Returns the list of statistics for the network
getVisibleBiases        Returns the biases of the visible units.
getVisibleBiasesInc     Returns the update value for the biases of the
                        visible units.
getVisibleUnitStates    Returns a list with the states of the visible
                        units.
getWeightCost           Returns the weigth cost for the training
getWeightInc            Returns the update value for the weights.
getWeights              Returns the weigths of the 'RBM'.
linearUnit              Linear unit function.
linearUnitDerivative    Linear unit function with unit derivatives.
linearUnitFunc          Calculates the linear neuron output no transfer
                        function
loadDArch               Loads a DArch network
loadRBM                 Loads a RBM network
loadRBMFFWeights        Loads weigths and biases for a RBM network from
                        a ffData file.
makeStartEndPoints      Makes start- and end-points for the batches.
minimize                Minimize a differentiable multivariate
                        function.
minimizeAutoencoder     Conjugate gradient for a autoencoder network
minimizeClassifier      Conjugate gradient for a classification network
mseError                Mean quared error function
newDArch                Constructor function for 'DArch' objects.
newRBM                  Constructor function for RBM object.
preTrainDArch           Pre trains a 'DArch' network
quadraticError          Quadratic error function
rbmUpdate               Function for updating the weights and biases of
                        an 'RBM'
readMNIST               Function for generating ff files of the MNIST
                        Database
removeLayerField        Removes a layer from the 'DArch' object
resetDArch              Resets the weights and biases of the 'DArch'
                        object
resetExecOutput         Resets the output list of the 'DArch' object
resetRBM                Resets the weights and biases of the 'RBM'
                        object
rpropagation            Resilient-Backpropgation training for deep
                        architectures.
runDArch                Execute the darch
saveDArch               Saves a DArch network
saveRBM                 Saves a RBM network
saveRBMFFWeights        Saves weights and biases of a RBM network into
                        a ffData file.
setBatchSize<-          Sets the batch size of the 'Net'.
setCancel<-             Set whether the learning shall be canceled.
setCancelMessage<-      Sets the cancel message.
setErrorFunction<-      Sets the error function of the 'Net'.
setExecuteFunction<-    Sets the execution function for the network
setFF<-                 Sets if the weights are saved as ff objects
setFinalMomentum<-      Sets the final momentum of the 'Net'.
setFineTuneFunction<-   Sets the fine tuning function for the network
setGenWeightFunction<-
                        Sets the function for generating weight
                        matrices.
setHiddenBiases<-       Sets the biases of the hidden units for the
                        'RBM' object
setHiddenBiasesInc<-    Sets the update value for the biases of the
                        hidden units
setHiddenUnitFunction<-
                        Sets the unit function of the hidden units
setHiddenUnitStates<-   Sets the states of the hidden units
setLayer<-              Sets a layer with the given index for the
                        network
setLayerField<-         Sets a field in a layer.
setLayerFunction<-      Sets the function for a layer with the given
                        index
setLayerWeights<-       Sets the weights of a layer with the given
                        index
setLayers<-             Sets the layers for the network
setLearnRateBiasHidden<-
                        Sets the learnig rates of the biases for the
                        hidden units
setLearnRateBiasVisible<-
                        Sets the learnig rates of the biases for the
                        visible units
setLearnRateBiases<-    Sets the learning rate for the biases
setLearnRateWeights<-   Sets the learning rate for the weights.
setLogLevel<-           Sets the log level for the 'Net'.
setMomentum<-           Sets the momentum of the 'Net'.
setMomentumSwitch<-     Sets the momentum switch of the 'Net'.
setNumHidden<-          Sets the number of hidden units
setNumVisible<-         Sets the number of visible units
setOutput<-             Sets the output of the 'RBM' object
setPosPhaseData<-       Sets the positive phase data for the training
setRBMList<-            Sets the list of RBMs
setStats<-              Adds a list of statistics to the network
setUpdateFunction<-     Sets the update function of the 'RBM' object
setVisibleBiases<-      Sets the biases of the visible units for the
                        'RBM' object
setVisibleBiasesInc<-   Sets the update value for the biases of the
                        visible units
setVisibleUnitFunction<-
                        Sets the unit function of the visible units
setVisibleUnitStates<-
                        Sets the states of the visible units
setWeightCost<-         Sets the weight costs for the training
setWeightInc<-          Sets the update values for the weights
setWeights<-            Sets the weights of the 'RBM' object
sigmUnitFunc            Calculates the neuron output with the sigmoid
                        function
sigmUnitFuncSwitch      Calculates the neuron output with the sigmoid
                        function
sigmoidUnit             Sigmoid unit function.
sigmoidUnitDerivative   Sigmoid unit function with unit derivatives.
softmaxUnit             Softmax unit function.
softmaxUnitDerivative   Softmax unit function with unit derivatives.
trainRBM                Trains a 'RBM' with contrastive divergence
