Returns the execution output of the layer from the DArch Constructor function for RBM object.
Binary sigmoid unit function.
Returns the number of visible units of the RBM Deep architectures in R
Returns the function for generating weight matrices.
Returns the cancel value.
Returns the list of statistics for the network
Pre trains a DArch Returns the data for the positive phaes.
Returns the learning rate for the visible biases.
Adds a field to a layer
Sets the error function of the Net Cross entropy error function
Abtract class for neural networks.
Returns the learning rate for the bias weigths of the DArch Returns the function for the execution of the DArch Resets the weights and biases of the RBM Returns if the weights are saved as ff objects
Function for generating ff files of the MNIST Database
Calculates the linear neuron output no transfer function
Returns the biases of the hidden units.
Minimize a differentiable multivariate function.
Returns the execution output list of the
DArch Class for Restricted-Bolzmann-Machine
Returns the error function of the Net Fine tuning function for the deep architecture.
Returns the fine tune function for the DArch Conjugate gradient for a autoencoder network
Generates a weight matrix.
Generates the rbm's for the pre-training.
Returns the cancel message.
Returns the output of the RBM Adds a layer to the DArch object
Sets the positive phase data for the training
Sets the execution function for the network
Sets the layers for the network
Sets the final momentum of the Net Sigmoid unit function with unit derivatives.
Function for updating the weights and biases of an RBM Returns the field of a layer from the
DArch Returns the learning rate for the hidden biases.
Returns the final momentum of the Net Returns the update value for the biases of the hidden units.
Returns the learn rate of the weights.
Returns a list of RBM DArch Sets the momentum of the Net Returns the momentum of the Net Returns the update value for the biases of the visible units.
Softmax unit function with unit derivatives.
Returns the weights of a layer from the
DArch Sets the log level for the Net Mean quared error function
Returns the a list of layers from the DArch Sets the update value for the biases of the visible units
Saves a RBM network
Adds an execution output for a DArch object
Sets the number of visible units
Returns the update value for the weights.
Returns the number of hidden units of the RBM Linear unit function with unit derivatives.
setLearnRateBiasVisible<-
Sets the learnig rates of the biases for the visible units
Calculates the neuron output with the sigmoid function
Returns the biases of the visible units.
Loads a RBM network
Saves a DArch network
Constructor function for DArch Execute the darch
Sets a layer with the given index for the network
Sets the update value for the biases of the hidden units
Sets the biases of the hidden units for the RBM Conjugate gradient for a classification network
Sets the cancel message.
Sets the unit function of the hidden units
Sets the learnig rates of the biases for the hidden units
Loads weigths and biases for a RBM network from a ffData file.
Sets the list of RBMs
Sets the number of hidden units
Removes a layer from the DArch Loads a DArch network
Sets the momentum switch of the Net Sets the function for a layer with the given index
Returns the weigth cost for the training
Resilient-Backpropgation training for deep architectures.
Sets the unit function of the visible units
Sets the fine tuning function for the network
Sets the weights of the RBM Returns a list with the states of the visible units.
Makes start- and end-points for the batches.
Returns the neuron function of a layer from the
DArch Backpropagation learning function
Linear unit function.
Sigmoid unit function.
Sets the biases of the visible units for the RBM Sets the batch size of the Net Resets the output list of the DArch Sets the update values for the weights
Sets the learning rate for the weights.
Softmax unit function.
Adds a list of statistics to the network
Set whether the learning shall be canceled.
Sets the weights of a layer with the given index
Sets the states of the hidden units
Sets the weight costs for the training
Quadratic error function
Sets the states of the visible units
Resets the weights and biases of the DArch Sets if the weights are saved as ff objects
Returns the weigths of the RBM Saves weights and biases of a RBM network into a ffData file.
Sets the function for generating weight matrices.
Sets the update function of the RBM Returns the batch size of the Net Sets the output of the RBM Sets the learning rate for the biases
Trains a RBM Returns a layer from the DArch Returns a list with the states of the hidden units.
Returns the momentum switch of the Net Calculates the neuron output with the sigmoid function
Sets a field in a layer.
Returns the logger of the Net Sets the logger of the Net