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Creates a neuron according to the structure established by the AMORE package standard.
● Data Source:
CranContrib
● Keywords: neural
● Alias: init.MLPneuron
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0 images
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random.init.MLPnet
(Package: AMORE) :
Initialize the network with random weigths and biases.
Provides random values to the network weights and biases so as to start with. Basically it applies the random.init.MLPneuron function to every neuron in the network.
● Data Source:
CranContrib
● Keywords: neural
● Alias: random.init.MLPnet
●
0 images
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newff
(Package: AMORE) :
Create a Multilayer Feedforward Neural Network
Creates a feedforward artificial neural network according to the structure established by the AMORE package standard.
● Data Source:
CranContrib
● Keywords: neural
● Alias: newff
●
1 images
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graphviz.MLPnet
(Package: AMORE) :
Neural network graphic representation
Creates a dot file, suitable to be processed with graphviz, containing a graphical representation of the netwok topology and some numerical information about the network parameters.
● Data Source:
CranContrib
● Keywords: neural
● Alias: graphviz.MLPnet
●
0 images
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ADAPTgd.MLPnet
(Package: AMORE) :
Adaptative gradient descent training
Adaptative gradient descent training method.
● Data Source:
CranContrib
● Keywords: neural
● Alias: ADAPTgd.MLPnet
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0 images
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random.init.MLPneuron
(Package: AMORE) :
Initialize the neuron with random weigths and bias.
Provides random values to the neuron weights and bias so as to start with. It is usually called by the random.init.NeuralNet function during the construction of the neural object by the newff function.
● Data Source:
CranContrib
● Keywords: neural
● Alias: random.init.MLPneuron
●
0 images
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training.report
(Package: AMORE) :
Neural network training report generator function.
Function in charge of reporting the behavior of the network training. The users should modify this function according to their needs.
● Data Source:
CranContrib
● Keywords: neural
● Alias: training.report
●
0 images
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select.activation.function
(Package: AMORE) :
Provides R code of the selected activation function.
Provides random values to the neuron weights and bias so as to start with. It is usually called by the random.init.NeuralNet function during the construction of the neural object by the newff function.
● Data Source:
CranContrib
● Keywords: neural
● Alias: select.activation.function
●
0 images
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train
(Package: AMORE) :
Neural network training function.
For a given data set (training set), this function modifies the neural network weights and biases to approximate the relationships amongst variables present in the training set. These may serve to satisfy several needs, i.e. fitting non-linear functions.
● Data Source:
CranContrib
● Keywords: neural
● Alias: train
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0 images
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sim.MLPnet
(Package: AMORE) :
Performs the simulation of a neural network from an input data set.
This function calculates the output values of the neural network for a given data set. Various versions are provided according to different degrees of C code conversion. The sim.MLPnet function is the latest and quickest.
● Data Source:
CranContrib
● Keywords: neural
● Alias: sim, sim.MLPnet
●
0 images
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providing 
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