C# Class FANNCSharp.Float.NeuralNet

Inheritance: IDisposable
Exibir arquivo Open project: joelself/FannCSharp Class Usage Examples

Private Properties

Property Type Description
InternalCallback int
NeuralNet System

Public Methods

Method Description
CascadetrainOnData ( TrainingData data, uint maxNeurons, uint neuronsBetweenReports, float desiredError ) : void
CascadetrainOnFile ( string filename, uint maxNeurons, uint neuronsBetweenReports, float desiredError ) : void
ClearScalingParams ( ) : bool
DescaleInput ( float input ) : void
DescaleOutput ( float output ) : void
DescaleTrain ( TrainingData data ) : void
DisableSeedRand ( ) : void
Dispose ( ) : void
EnableSeedRand ( ) : void
GetActivationFunction ( int layer, int neuron ) : ActivationFunction
GetActivationSteepness ( int layer, int neuron ) : float
InitWeights ( TrainingData data ) : void
NeuralNet ( NetworkType netType, ICollection layers ) : System
NeuralNet ( NetworkType netType, uint numLayers ) : System
NeuralNet ( NeuralNet other ) : System
NeuralNet ( float connectionRate, ICollection layers ) : System
NeuralNet ( float connectionRate, uint numLayers ) : System
NeuralNet ( string filename ) : System
PrintConnections ( ) : void
PrintError ( ) : void
PrintParameters ( ) : void
RandomizeWeights ( float minWeight, float maxWeight ) : void
ResetErrno ( ) : void
ResetErrstr ( ) : void
ResetMSE ( ) : void
Run ( DataAccessor input ) : float[]
Run ( float input ) : float[]
Save ( string file ) : bool
SaveToFixed ( string file ) : int
ScaleInput ( DataAccessor input ) : void
ScaleOutput ( DataAccessor output ) : void
ScaleTrain ( TrainingData data ) : void
SetActivationFunction ( ActivationFunction function, int layer, int neuron ) : void
SetActivationFunctionLayer ( ActivationFunction function, int layer ) : void
SetActivationSteepness ( float steepness, int layer, int neuron ) : void
SetActivationSteepnessLayer ( float steepness, int layer ) : void
SetCallback ( TrainingCallback callback, Object userData ) : void
SetInputScalingParams ( TrainingData data, float newInputMin, float newInputMax ) : bool
SetOutputScalingParams ( TrainingData data, float newOutputMin, float newOutputMax ) : bool
SetScalingParams ( TrainingData data, float newInputMin, float newInputMax, float newOutputMin, float newOutputMax ) : bool
SetWeight ( uint fromNeuron, uint toNeuron, float weight ) : void
Test ( float input, float desiredOutput ) : float[]
TestData ( TrainingData data ) : float
TestDataParallel ( TrainingData data, uint threadNumb ) : float
TestDataParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
Train ( float input, float desiredOutput ) : void
TrainEpoch ( TrainingData data ) : float
TrainEpochBatchParallel ( TrainingData data, uint threadNumb ) : float
TrainEpochBatchParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
TrainEpochIncrementalMod ( TrainingData data ) : float
TrainEpochIncrementalMod ( TrainingData data, List predictedOutputs ) : float
TrainEpochIrpropmParallel ( TrainingData data, uint threadNumb ) : float
TrainEpochIrpropmParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
TrainEpochQuickpropParallel ( TrainingData data, uint threadNumb ) : float
TrainEpochQuickpropParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
TrainEpochSarpropParallel ( TrainingData data, uint threadNumb ) : float
TrainEpochSarpropParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
TrainOnData ( TrainingData data, uint maxEpochs, uint epochsBetweenReports, float desiredError ) : void
TrainOnFile ( string filename, uint maxEpochs, uint epochsBetweenReports, float desiredError ) : void

Private Methods

Method Description
InternalCallback ( global netPtr, global dataPtr, uint max_epochs, uint epochs_between_reports, float desired_error, uint epochs, global user_data ) : int
NeuralNet ( neural_net other ) : System

Method Details

CascadetrainOnData() public method

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

CascadetrainOnFile() public method

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

ClearScalingParams() public method

public ClearScalingParams ( ) : bool
return bool

DescaleInput() public method

public DescaleInput ( float input ) : void
input float
return void

DescaleOutput() public method

public DescaleOutput ( float output ) : void
output float
return void

DescaleTrain() public method

public DescaleTrain ( TrainingData data ) : void
data TrainingData
return void

DisableSeedRand() public method

public DisableSeedRand ( ) : void
return void

Dispose() public method

public Dispose ( ) : void
return void

EnableSeedRand() public method

public EnableSeedRand ( ) : void
return void

GetActivationFunction() public method

public GetActivationFunction ( int layer, int neuron ) : ActivationFunction
layer int
neuron int
return ActivationFunction

GetActivationSteepness() public method

public GetActivationSteepness ( int layer, int neuron ) : float
layer int
neuron int
return float

InitWeights() public method

public InitWeights ( TrainingData data ) : void
data TrainingData
return void

NeuralNet() public method

public NeuralNet ( NetworkType netType, ICollection layers ) : System
netType NetworkType
layers ICollection
return System

NeuralNet() public method

public NeuralNet ( NetworkType netType, uint numLayers ) : System
netType NetworkType
numLayers uint
return System

NeuralNet() public method

public NeuralNet ( NeuralNet other ) : System
other NeuralNet
return System

NeuralNet() public method

public NeuralNet ( float connectionRate, ICollection layers ) : System
connectionRate float
layers ICollection
return System

NeuralNet() public method

public NeuralNet ( float connectionRate, uint numLayers ) : System
connectionRate float
numLayers uint
return System

NeuralNet() public method

public NeuralNet ( string filename ) : System
filename string
return System

PrintConnections() public method

public PrintConnections ( ) : void
return void

PrintError() public method

public PrintError ( ) : void
return void

PrintParameters() public method

public PrintParameters ( ) : void
return void

RandomizeWeights() public method

public RandomizeWeights ( float minWeight, float maxWeight ) : void
minWeight float
maxWeight float
return void

ResetErrno() public method

public ResetErrno ( ) : void
return void

ResetErrstr() public method

public ResetErrstr ( ) : void
return void

ResetMSE() public method

public ResetMSE ( ) : void
return void

Run() public method

public Run ( DataAccessor input ) : float[]
input DataAccessor
return float[]

Run() public method

public Run ( float input ) : float[]
input float
return float[]

Save() public method

public Save ( string file ) : bool
file string
return bool

SaveToFixed() public method

public SaveToFixed ( string file ) : int
file string
return int

ScaleInput() public method

public ScaleInput ( DataAccessor input ) : void
input DataAccessor
return void

ScaleOutput() public method

public ScaleOutput ( DataAccessor output ) : void
output DataAccessor
return void

ScaleTrain() public method

public ScaleTrain ( TrainingData data ) : void
data TrainingData
return void

SetActivationFunction() public method

public SetActivationFunction ( ActivationFunction function, int layer, int neuron ) : void
function ActivationFunction
layer int
neuron int
return void

SetActivationFunctionLayer() public method

public SetActivationFunctionLayer ( ActivationFunction function, int layer ) : void
function ActivationFunction
layer int
return void

SetActivationSteepness() public method

public SetActivationSteepness ( float steepness, int layer, int neuron ) : void
steepness float
layer int
neuron int
return void

SetActivationSteepnessLayer() public method

public SetActivationSteepnessLayer ( float steepness, int layer ) : void
steepness float
layer int
return void

SetCallback() public method

public SetCallback ( TrainingCallback callback, Object userData ) : void
callback TrainingCallback
userData Object
return void

SetInputScalingParams() public method

public SetInputScalingParams ( TrainingData data, float newInputMin, float newInputMax ) : bool
data TrainingData
newInputMin float
newInputMax float
return bool

SetOutputScalingParams() public method

public SetOutputScalingParams ( TrainingData data, float newOutputMin, float newOutputMax ) : bool
data TrainingData
newOutputMin float
newOutputMax float
return bool

SetScalingParams() public method

public SetScalingParams ( TrainingData data, float newInputMin, float newInputMax, float newOutputMin, float newOutputMax ) : bool
data TrainingData
newInputMin float
newInputMax float
newOutputMin float
newOutputMax float
return bool

SetWeight() public method

public SetWeight ( uint fromNeuron, uint toNeuron, float weight ) : void
fromNeuron uint
toNeuron uint
weight float
return void

Test() public method

public Test ( float input, float desiredOutput ) : float[]
input float
desiredOutput float
return float[]

TestData() public method

public TestData ( TrainingData data ) : float
data TrainingData
return float

TestDataParallel() public method

public TestDataParallel ( TrainingData data, uint threadNumb ) : float
data TrainingData
threadNumb uint
return float

TestDataParallel() public method

public TestDataParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
data TrainingData
threadNumb uint
predictedOutputs List
return float

Train() public method

public Train ( float input, float desiredOutput ) : void
input float
desiredOutput float
return void

TrainEpoch() public method

public TrainEpoch ( TrainingData data ) : float
data TrainingData
return float

TrainEpochBatchParallel() public method

public TrainEpochBatchParallel ( TrainingData data, uint threadNumb ) : float
data TrainingData
threadNumb uint
return float

TrainEpochBatchParallel() public method

public TrainEpochBatchParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
data TrainingData
threadNumb uint
predictedOutputs List
return float

TrainEpochIncrementalMod() public method

public TrainEpochIncrementalMod ( TrainingData data ) : float
data TrainingData
return float

TrainEpochIncrementalMod() public method

public TrainEpochIncrementalMod ( TrainingData data, List predictedOutputs ) : float
data TrainingData
predictedOutputs List
return float

TrainEpochIrpropmParallel() public method

public TrainEpochIrpropmParallel ( TrainingData data, uint threadNumb ) : float
data TrainingData
threadNumb uint
return float

TrainEpochIrpropmParallel() public method

public TrainEpochIrpropmParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
data TrainingData
threadNumb uint
predictedOutputs List
return float

TrainEpochQuickpropParallel() public method

public TrainEpochQuickpropParallel ( TrainingData data, uint threadNumb ) : float
data TrainingData
threadNumb uint
return float

TrainEpochQuickpropParallel() public method

public TrainEpochQuickpropParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
data TrainingData
threadNumb uint
predictedOutputs List
return float

TrainEpochSarpropParallel() public method

public TrainEpochSarpropParallel ( TrainingData data, uint threadNumb ) : float
data TrainingData
threadNumb uint
return float

TrainEpochSarpropParallel() public method

public TrainEpochSarpropParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
data TrainingData
threadNumb uint
predictedOutputs List
return float

TrainOnData() public method

public TrainOnData ( TrainingData data, uint maxEpochs, uint epochsBetweenReports, float desiredError ) : void
data TrainingData
maxEpochs uint
epochsBetweenReports uint
desiredError float
return void

TrainOnFile() public method

public TrainOnFile ( string filename, uint maxEpochs, uint epochsBetweenReports, float desiredError ) : void
filename string
maxEpochs uint
epochsBetweenReports uint
desiredError float
return void