| M | |
| MaxInput | |
| MaxOutput | |
| MergeTrainData | |
| MinInput | |
| MinOutput | |
| MoveNext, FANNCSharp. | |
| MSE | |
| Multiplier, FANNCSharp. | |
| N | |
| NetworkType | |
| NetworkType.cs | |
| NeuralNet | |
| O | |
| Output | |
| OutputAccessor | |
| OutputCount | |
| P | |
| PrintConnections | |
| PrintError | |
| PrintParameters | |
| Properties | |
| Q | |
| QuickpropDecay | |
| QuickpropMu |
Get the maximum value of all in the input data
public double MaxInput { get }
Get the maximum value of all in the input data
public float MaxInput { get }
Get the maximum value of all in the output data
public double MaxOutput { get }
Get the maximum value of all in the output data
public float MaxOutput { get }
Merges the data into the data contained in the TrainingData.
public void MergeTrainData( TrainingData data )
Merges the data into the data contained in the TrainingData.
public void MergeTrainData( TrainingData data )
Merges the data into the data contained in the TrainingData.
public void MergeTrainData( TrainingData data )
Get the minimum value of all in the input data
public double MinInput { get }
Get the minimum value of all in the input data
public float MinInput { get }
Get the minimum value of all in the output data
public double MinOutput { get }
Get the minimum value of all in the output data
public float MinOutput { get }
Moves the internal reference to the next item in the collection
public bool MoveNext()
Reads the mean square error from the network.
public float MSE { get }
Reads the mean square error from the network.
public float MSE { get }
Reads the mean square error from the network.
public float MSE { get }
Returns the multiplier that fix point data is multiplied with.
public uint Multiplier { get }
Get the type of neural network it was created as.
public NetworkType NetworkType { get }
Get the type of neural network it was created as.
public NetworkType NetworkType { get }
Get the type of neural network it was created as.
public NetworkType NetworkType { get }
Creates a copy the other NeuralNet.
public NeuralNet( NeuralNet other )
Creates a copy the other NeuralNet.
public NeuralNet( NeuralNet other )
Creates a copy the other NeuralNet.
public NeuralNet( NeuralNet other )
Grant access to the encapsulated data since many situations and applications creates the data from sources other than files or uses the training data for testing and related functions.
public double[][] Output { get }
Grant access to the encapsulated data since many situations and applications creates the data from sources other than files or uses the training data for testing and related functions.
public int[][] Output { get }
Grant access to the encapsulated data since many situations and applications creates the data from sources other than files or uses the training data for testing and related functions.
public float[][] Output { get }
An alternative to Output that returns an accessor object that grants access to to the input data with no copying.
public ArrayAccessor OutputAccessor { get }
An alternative to Output that returns an accessor object that grants access to to the input data with no copying.
public ArrayAccessor OutputAccessor { get }
An alternative to Output that returns an accessor object that grants access to to the input data with no copying.
public ArrayAccessor OutputAccessor { get }
Get the number of output neurons.
public uint OutputCount { get }
Returns the number of outputs in each of the training patterns in the TrainingData.
public uint OutputCount { get }
Get the number of output neurons.
public uint OutputCount { get }
Returns the number of outputs in each of the training patterns in the TrainingData.
public uint OutputCount { get }
Get the number of output neurons.
public uint OutputCount { get }
Returns the number of outputs in each of the training patterns in the TrainingData.
public uint OutputCount { get }
Will print the connections of the network in a compact matrix, for easy viewing of the internals of the network.
public void PrintConnections()
Will print the connections of the network in a compact matrix, for easy viewing of the internals of the network.
public void PrintConnections()
Will print the connections of the network in a compact matrix, for easy viewing of the internals of the network.
public void PrintConnections()
Prints the last error to Console.Error.
public void PrintError()
Prints the last error to Console.Error.
public void PrintError()
Prints the last error to Console.Error.
public void PrintError()
Prints all of the parameters and options of the neural network
public void PrintParameters()
Prints all of the parameters and options of the neural network
public void PrintParameters()
Prints all of the parameters and options of the neural network
public void PrintParameters()
Gets or sets the quickprop decay factor.
public float QuickpropDecay { get, set }
Gets or sets the quickprop decay factor.
public float QuickpropDecay { get, set }
Gets or sets the quickprop decay factor.
public float QuickpropDecay { get, set }
Get or sets the quickprop mu factor.
public float QuickpropMu { get, set }
Get or sets the quickprop mu factor.
public float QuickpropMu { get, set }
Get or sets the quickprop mu factor.
public float QuickpropMu { get, set }