C# Класс Encog.Neural.NeuralData.Temporal.TemporalNeuralDataSet

This class implements a temporal neural data set. A temporal neural dataset is designed to use a neural network to predict. A temporal dataset is a stream of data over a time range. This time range is broken up into "points". Each point can contain one or more values. These values are either the values that you would like to predict, or use to predict. It is possible for a value to be both predicted and used to predict. For example, if you were trying to predict a trend in a stock's price fluctuations you might very well use the security price for both. Each point that we have data for is stored in the TemporalPoint class. Each TemporalPoint will contain one more data values. These data values are described by the TemporalDataDescription class. For example, if you had five TemporalDataDescription objects added to this class, each Temporal point object would contain five values. Points are arranged by sequence number. No two points can have the same sequence numbers. Methods are provided to allow you to add points using the Date class. These dates are resolved to sequence number using the level of granularity specified for this class. No two points can occupy the same granularity increment.

Наследование: Encog.Neural.Data.Basic.BasicNeuralDataSet

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Открытые методы

Метод	Описание
Add ( INeuralData data ) : void	Adding directly is not supported. Rather, add temporal points and generate the training data.
Add ( INeuralData inputData, INeuralData idealData ) : void	Adding directly is not supported. Rather, add temporal points and generate the training data.
Add ( INeuralDataPair inputData ) : void	Adding directly is not supported. Rather, add temporal points and generate the training data.
AddDescription ( TemporalDataDescription desc ) : void	Add a data description.
CalculateActualSetSize ( ) : int	Calculate the actual set size, this is the number of training set entries that will be generated.
CalculateNeuronCounts ( ) : void	Calculate how many input and output neurons will be needed for the current data.
CalculatePointsInRange ( ) : int	Calculate how many points are in the high and low range. These are the points that the training set will be generated on.
CalculateStartIndex ( ) : int	Calculate the index to start at.
Clear ( ) : void	Clear the entire dataset.
CreatePoint ( System.DateTime when ) : TemporalPoint	Create a temporal point from a time. Using the grandularity each date is given a unique sequence number. No two dates that fall in the same grandularity should be specified.
CreatePoint ( int sequence ) : TemporalPoint	Create a temporal data point using a sequence number. They can also be created using time. No two points should have the same sequence number.
Generate ( ) : void	Generate the training sets.
GenerateInputNeuralData ( int index ) : BasicNeuralData	Generate input neural data for the specified index.
GenerateOutputNeuralData ( int index ) : BasicNeuralData	Generate neural ideal data for the specified index.
GetSequenceFromDate ( System.DateTime when ) : int	Create a sequence number from a time. The first date will be zero, and subsequent dates will be increased according to the grandularity specified.
IsPointInRange ( TemporalPoint point ) : bool	Is the specified point within the range. If a point is in the selection range, then the point will be used to generate the training sets.
SortPoints ( ) : void	Sort the points.
TemporalNeuralDataSet ( int inputWindowSize, int predictWindowSize ) : System	Construct a dataset.

Приватные методы

Метод	Описание
FormatData ( TemporalDataDescription desc, int index ) : double	Format data according to the type specified in the description.
GetDataDeltaChange ( TemporalDataDescription desc, int index ) : double	Get data between two points in delta form.
GetDataPercentChange ( TemporalDataDescription desc, int index ) : double	Get data between two points in percent form.
GetDataRAW ( TemporalDataDescription desc, int index ) : double	Get data between two points in raw form.

Описание методов

Add() публичный Метод

Adding directly is not supported. Rather, add temporal points and generate the training data.

public Add ( INeuralData data ) : void
data	INeuralData	Not used.
Результат	void

Add() публичный Метод

Adding directly is not supported. Rather, add temporal points and generate the training data.

public Add ( INeuralData inputData, INeuralData idealData ) : void
inputData	INeuralData	Not used
idealData	INeuralData	Not used
Результат	void

Add() публичный Метод

Adding directly is not supported. Rather, add temporal points and generate the training data.

public Add ( INeuralDataPair inputData ) : void
inputData	INeuralDataPair	Not used.
Результат	void

AddDescription() публичный Метод

Add a data description.

public AddDescription ( TemporalDataDescription desc ) : void
desc	TemporalDataDescription	The data description to add.
Результат	void

CalculateActualSetSize() публичный Метод

Calculate the actual set size, this is the number of training set entries that will be generated.

public CalculateActualSetSize ( ) : int
Результат	int

CalculateNeuronCounts() публичный Метод

Calculate how many input and output neurons will be needed for the current data.

public CalculateNeuronCounts ( ) : void
Результат	void

CalculatePointsInRange() публичный Метод

Calculate how many points are in the high and low range. These are the points that the training set will be generated on.

public CalculatePointsInRange ( ) : int
Результат	int

CalculateStartIndex() публичный Метод

Calculate the index to start at.

public CalculateStartIndex ( ) : int
Результат	int

Clear() публичный Метод

Clear the entire dataset.

public Clear ( ) : void
Результат	void

CreatePoint() публичный Метод

Create a temporal point from a time. Using the grandularity each date is given a unique sequence number. No two dates that fall in the same grandularity should be specified.

public CreatePoint ( System.DateTime when ) : TemporalPoint
when	System.DateTime	The time that this point should be created at.
Результат	TemporalPoint

CreatePoint() публичный Метод

Create a temporal data point using a sequence number. They can also be created using time. No two points should have the same sequence number.

public CreatePoint ( int sequence ) : TemporalPoint
sequence	int	The sequence number.
Результат	TemporalPoint

Generate() публичный Метод

Generate the training sets.

public Generate ( ) : void
Результат	void

GenerateInputNeuralData() публичный Метод

Generate input neural data for the specified index.

public GenerateInputNeuralData ( int index ) : BasicNeuralData
index	int	The index to generate neural data for.
Результат	Encog.Neural.Data.Basic.BasicNeuralData

GenerateOutputNeuralData() публичный Метод

Generate neural ideal data for the specified index.

public GenerateOutputNeuralData ( int index ) : BasicNeuralData
index	int	The index to generate for.
Результат	Encog.Neural.Data.Basic.BasicNeuralData

GetSequenceFromDate() публичный Метод

Create a sequence number from a time. The first date will be zero, and subsequent dates will be increased according to the grandularity specified.

public GetSequenceFromDate ( System.DateTime when ) : int
when	System.DateTime	The date to generate the sequence number for.
Результат	int

IsPointInRange() публичный Метод

Is the specified point within the range. If a point is in the selection range, then the point will be used to generate the training sets.

public IsPointInRange ( TemporalPoint point ) : bool
point	TemporalPoint	The point to consider.
Результат	bool

SortPoints() публичный Метод

Sort the points.

public SortPoints ( ) : void
Результат	void

TemporalNeuralDataSet() публичный Метод

Construct a dataset.

public TemporalNeuralDataSet ( int inputWindowSize, int predictWindowSize ) : System
inputWindowSize	int	What is the input window size.
predictWindowSize	int	What is the prediction window size.
Результат	System