C# 클래스 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.

상속: Encog.Neural.Data.Basic.BasicNeuralDataSet

파일 보기 프로젝트 열기: encog/encog-silverlight-core

공개 메소드들

메소드	설명
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.

비공개 메소드들

메소드	설명
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.

메소드 상세

Add() 공개 메소드

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

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

Add() 공개 메소드

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
리턴	void

Add() 공개 메소드

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

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

AddDescription() 공개 메소드

Add a data description.

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

CalculateActualSetSize() 공개 메소드

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

public CalculateActualSetSize ( ) : int
리턴	int

CalculateNeuronCounts() 공개 메소드

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

public CalculateNeuronCounts ( ) : void
리턴	void

CalculatePointsInRange() 공개 메소드

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
리턴	int

CalculateStartIndex() 공개 메소드

Calculate the index to start at.

public CalculateStartIndex ( ) : int
리턴	int

Clear() 공개 메소드

Clear the entire dataset.

public Clear ( ) : void
리턴	void

CreatePoint() 공개 메소드

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.
리턴	TemporalPoint

CreatePoint() 공개 메소드

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.
리턴	TemporalPoint

Generate() 공개 메소드

Generate the training sets.

public Generate ( ) : void
리턴	void

GenerateInputNeuralData() 공개 메소드

Generate input neural data for the specified index.

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

GenerateOutputNeuralData() 공개 메소드

Generate neural ideal data for the specified index.

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

GetSequenceFromDate() 공개 메소드

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.
리턴	int

IsPointInRange() 공개 메소드

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.
리턴	bool

SortPoints() 공개 메소드

Sort the points.

public SortPoints ( ) : void
리턴	void

TemporalNeuralDataSet() 공개 메소드

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.
리턴	System