public void CascadetrainOnData( TrainingData  data, uint  maxNeurons, uint  neuronsBetweenReports, float  desiredError )

Trains on an entire dataset, for a period of time using the Cascade2 training algorithm.

public void CascadetrainOnData( TrainingData  data, uint  maxNeurons, uint  neuronsBetweenReports, float  desiredError )

Trains on an entire dataset, for a period of time using the Cascade2 training algorithm.

public void CascadetrainOnFile( string  filename, uint  maxNeurons, uint  neuronsBetweenReports, float  desiredError )

Does the same as CascadetrainOnData, but reads the training data directly from a file.

public void CascadetrainOnFile( string  filename, uint  maxNeurons, uint  neuronsBetweenReports, float  desiredError )

Does the same as CascadetrainOnData, but reads the training data directly from a file.

public bool ClearScalingParams()

Clears scaling parameters.

public bool ClearScalingParams()

Clears scaling parameters.

public Connection( uint  fromNeuron, uint  toNeuron, double  weight )

Creates a connection with the specified parameters Parameters: fromNeuron - Unique number used to identify source neuron toNeuron - Unique number used to identify destination neuron weight - The numerical value of the weight Example:

public Connection( uint  fromNeuron, uint  toNeuron, int  weight )

Creates a connection with the specified parameters Parameters: fromNeuron - Unique number used to identify source neuron toNeuron - Unique number used to identify destination neuron weight - The numerical value of the weight Example:

public Connection( uint  fromNeuron, uint  toNeuron, float  weight )

Creates a connection with the specified parameters Parameters: fromNeuron - Unique number used to identify source neuron toNeuron - Unique number used to identify destination neuron weight - The numerical value of the weight Example:

public void CreateTrainFromCallback( uint  dataCount, uint  inputCount, uint  outputCount, DataCreateCallback  callback )

Creates the training data from a user supplied function.

public void CreateTrainFromCallback( uint  dataCount, uint  inputCount, uint  outputCount, DataCreateCallback  callback )

Creates the training data from a user supplied function.

public void CreateTrainFromCallback( uint  dataCount, uint  inputCount, uint  outputCount, DataCreateCallback  callback )

Creates the training data from a user supplied function.

Scale data in input vector after get it from ann based on previously calculated parameters.

public void DescaleInput( float[]  input )

Scale data in input vector after get it from ann based on previously calculated parameters.

public void DescaleOutput( double[]  output )

Scale data in output vector after get it from ann based on previously calculated parameters.

public void DescaleOutput( float[]  output )

Scale data in output vector after get it from ann based on previously calculated parameters.

public void DescaleTrain( TrainingData  data )

Descale input and output data based on previously calculated parameters.

public void DescaleTrain( TrainingData  data )

Descale input and output data based on previously calculated parameters.

public void DisableSeedRand()

Disables the automatic random generator seeding that happens in FANN.

public void DisableSeedRand()

Disables the automatic random generator seeding that happens in FANN.

public void DisableSeedRand()

Disables the automatic random generator seeding that happens in FANN.

Destructs the accessor.

Destructs the accessor.

public void Dispose()

Disposes the enumerator

public void Dispose()

Destructs the connection.

public void Dispose()

Destructs the entire network.

public void Dispose()

Disposes of the training data.

public void Dispose()

Closes the file

public void Dispose()

Destructs the connection.

public void Dispose()

Destructs the entire network.

public void Dispose()

Disposes of the training data.

public void Dispose()

Destructs the connection.

public void Dispose()

Destructs the entire network.

public void Dispose()

Disposes of the training data.

public void EnableSeedRand()

Enables the automatic random generator seeding that happens in FANN.

public void EnableSeedRand()

Enables the automatic random generator seeding that happens in FANN.

public void EnableSeedRand()

Enables the automatic random generator seeding that happens in FANN.

public FannFile( string  filename, string  mode )

Encapsulates a C FILE pointer

public ActivationFunction GetActivationFunction( int  layer, int  neuron )

Get the activation function for neuron number neuron in layer number layer, counting the input layer as layer 0.

public ActivationFunction GetActivationFunction( int  layer, int  neuron )

Get the activation function for neuron number neuron in layer number layer, counting the input layer as layer 0.

public ActivationFunction GetActivationFunction( int  layer, int  neuron )

Get the activation function for neuron number neuron in layer number layer, counting the input layer as layer 0.

public double GetActivationSteepness( int  layer, int  neuron )

Get the activation steepness for neuron number neuron in layer number layer, counting the input layer as layer 0.

public int GetActivationSteepness( int  layer, int  neuron )

Get the activation steepness for neuron number neuron in layer number layer, counting the input layer as layer 0.

public float GetActivationSteepness( int  layer, int  neuron )

Get the activation steepness for neuron number neuron in layer number layer, counting the input layer as layer 0.

Returns an enumerator that can enumerate over the collection of DataAccessors

Returns an enumerator that can enumerate over the collection of ints

public DataAccessor GetTrainInput( uint  position )

Gets the training input data at the given position

public DataAccessor GetTrainInput( uint  position )

Gets the training input data at the given position

public DataAccessor GetTrainInput( uint  position )

Gets the training input data at the given position

public DataAccessor GetTrainOutput( uint  position )

Gets the training output data at the given position

public DataAccessor GetTrainOutput( uint  position )

Gets the training output data at the given position

public DataAccessor GetTrainOutput( uint  position )

Gets the training output data at the given position

public void InitWeights( TrainingData  data )

Initialize the weights using Widrow + Nguyen’s algorithm.

public void InitWeights( TrainingData  data )

Initialize the weights using Widrow + Nguyen’s algorithm.

public void InitWeights( TrainingData  data )

Initialize the weights using Widrow + Nguyen’s algorithm.

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 )

Merges the data into the data contained in the TrainingData.

public bool MoveNext()

Moves the internal reference to the next item in the collection