TemporalMLDataSet (encog-java-core 3.4 API)

java.lang.Object
- org.encog.ml.data.basic.BasicMLDataSet
- - org.encog.neural.data.basic.BasicNeuralDataSet
  - - org.encog.ml.data.temporal.TemporalMLDataSet

All Implemented Interfaces:

java.io.Serializable, java.lang.Iterable<MLDataPair>, MLDataSet, NeuralDataSet

Direct Known Subclasses:

MarketMLDataSet
```
public class TemporalMLDataSet
extends BasicNeuralDataSet
implements java.io.Serializable
```
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.

See Also:

Serialized Form

Nested Class Summary
- Nested classes/interfaces inherited from class org.encog.ml.data.basic.BasicMLDataSet
  BasicMLDataSet.BasicMLIterator

Field Summary

Fields
Modifier and Type Field and Description

static java.lang.String ADD_NOT_SUPPORTED
Error message: adds are not supported.

Fields
Modifier and Type	Field and Description
`static java.lang.String`	`ADD_NOT_SUPPORTED` Error message: adds are not supported.

Constructor Summary

Constructors
Constructor and Description

TemporalMLDataSet(int inputWindowSize, int predictWindowSize)
Construct a dataset.

Constructors
Constructor and Description
`TemporalMLDataSet(int inputWindowSize, int predictWindowSize)` Construct a dataset.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`add(MLData data)` Adding directly is not supported.
`void`	`add(MLData inputData, MLData idealData)` Adding directly is not supported.
`void`	`add(MLDataPair inputData)` Adding directly is not supported.
`void`	`addDescription(TemporalDataDescription desc)` Add a data description.
`int`	`calculateActualSetSize()` Calculate the actual set size, this is the number of training set entries that will be generated.
`void`	`calculateNeuronCounts()` Calculate how many input and output neurons will be needed for the current data.
`int`	`calculatePointsInRange()` Calculate how many points are in the high and low range.
`int`	`calculateStartIndex()` Calculate the index to start at.
`void`	`clear()` Clear the entire dataset.
`TemporalPoint`	`createPoint(java.util.Date when)` Create a temporal point from a time.
`TemporalPoint`	`createPoint(int sequence)` Create a temporal data point using a sequence number.
`void`	`generate()` Generate the training sets.
`BasicNeuralData`	`generateInputNeuralData(int index)` Generate input neural data for the specified index.
`BasicNeuralData`	`generateOutputNeuralData(int index)` Generate neural ideal data for the specified index.
`java.util.List<TemporalDataDescription>`	`getDescriptions()`
`int`	`getDesiredSetSize()`
`int`	`getHighSequence()`
`int`	`getInputNeuronCount()`
`int`	`getInputWindowSize()`
`int`	`getLowSequence()`
`int`	`getOutputNeuronCount()`
`java.util.List<TemporalPoint>`	`getPoints()`
`int`	`getPredictWindowSize()`
`int`	`getSequenceFromDate(java.util.Date when)` Create a sequence number from a time.
`TimeUnit`	`getSequenceGrandularity()`
`java.util.Date`	`getStartingPoint()`
`boolean`	`isPointInRange(TemporalPoint point)` Is the specified point within the range.
`void`	`setDesiredSetSize(int desiredSetSize)`
`void`	`setHighSequence(int highSequence)`
`void`	`setInputWindowSize(int inputWindowSize)`
`void`	`setLowSequence(int lowSequence)`
`void`	`setPredictWindowSize(int predictWindowSize)`
`void`	`setSequenceGrandularity(TimeUnit sequenceGrandularity)`
`void`	`setStartingPoint(java.util.Date startingPoint)`
`void`	`sortPoints()` Sort the points.

Methods inherited from class org.encog.ml.data.basic.BasicMLDataSet
clone, close, get, getData, getIdealSize, getInputSize, getRecord, getRecordCount, isSupervised, iterator, openAdditional, setData, size, toList

Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.encog.ml.data.MLDataSet
close, get, getIdealSize, getInputSize, getRecord, getRecordCount, isSupervised, openAdditional, size

Methods inherited from interface java.lang.Iterable
forEach, iterator, spliterator

- Field Detail
  - ADD_NOT_SUPPORTED
```
public static final java.lang.String ADD_NOT_SUPPORTED
```
    Error message: adds are not supported.
    
    See Also:
    
    Constant Field Values
- Constructor Detail
  - TemporalMLDataSet
```
public TemporalMLDataSet(int inputWindowSize,
                         int predictWindowSize)
```
    Construct a dataset.
    
    Parameters:
    
    inputWindowSize - What is the input window size.
    
    predictWindowSize - What is the prediction window size.
- Method Detail
  - add
```
public void add(MLData data)
```
    Adding directly is not supported. Rather, add temporal points and generate the training data.
    
    Specified by:
    
    add in interface MLDataSet
    
    Overrides:
    
    add in class BasicMLDataSet
    
    Parameters:
    
    data - Not used.
  - add
```
public void add(MLData inputData,
                MLData idealData)
```
    Adding directly is not supported. Rather, add temporal points and generate the training data.
    
    Specified by:
    
    add in interface MLDataSet
    
    Overrides:
    
    add in class BasicMLDataSet
    
    Parameters:
    
    inputData - Not used.
    
    idealData - Not used.
  - add
```
public void add(MLDataPair inputData)
```
    Adding directly is not supported. Rather, add temporal points and generate the training data.
    
    Specified by:
    
    add in interface MLDataSet
    
    Overrides:
    
    add in class BasicMLDataSet
    
    Parameters:
    
    inputData - Not used.
  - addDescription
```
public void addDescription(TemporalDataDescription desc)
```
    Add a data description.
    
    Parameters:
    
    desc - The data description to add.
  - calculateActualSetSize
```
public int calculateActualSetSize()
```
    Calculate the actual set size, this is the number of training set entries that will be generated.
    
    Returns:
    
    The size of the training set.
  - calculateNeuronCounts
```
public void calculateNeuronCounts()
```
    Calculate how many input and output neurons will be needed for the current data.
  - calculatePointsInRange
```
public int calculatePointsInRange()
```
    Calculate how many points are in the high and low range. These are the points that the training set will be generated on.
    
    Returns:
    
    The number of points.
  - calculateStartIndex
```
public int calculateStartIndex()
```
    Calculate the index to start at.
    
    Returns:
    
    the starting index.
  - clear
```
public void clear()
```
    Clear the entire dataset.
  - createPoint
```
public TemporalPoint createPoint(java.util.Date when)
```
    Create a temporal point from a time. Using the granularity each date is given a unique sequence number. No two dates that fall in the same granularity should be specified.
    
    Parameters:
    
    when - The time that this point should be created at.
    
    Returns:
    
    The point TemporalPoint created.
  - createPoint
```
public TemporalPoint createPoint(int sequence)
```
    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.
    
    Parameters:
    
    sequence - The sequence number.
    
    Returns:
    
    A new TemporalPoint object.
  - generate
```
public void generate()
```
    Generate the training sets.
  - generateInputNeuralData
```
public BasicNeuralData generateInputNeuralData(int index)
```
    Generate input neural data for the specified index.
    
    Parameters:
    
    index - The index to generate neural data for.
    
    Returns:
    
    The input neural data generated.
  - generateOutputNeuralData
```
public BasicNeuralData generateOutputNeuralData(int index)
```
    Generate neural ideal data for the specified index.
    
    Parameters:
    
    index - The index to generate for.
    
    Returns:
    
    The neural data generated.
  - getDescriptions
```
public java.util.List<TemporalDataDescription> getDescriptions()
```
    Returns:
    
    A list of the data descriptions.
  - getDesiredSetSize
```
public int getDesiredSetSize()
```
    Returns:
    
    the desiredSetSize
  - getHighSequence
```
public int getHighSequence()
```
    Returns:
    
    the highSequence
  - getInputNeuronCount
```
public int getInputNeuronCount()
```
    Returns:
    
    the inputNeuronCount
  - getInputWindowSize
```
public int getInputWindowSize()
```
    Returns:
    
    the inputWindowSize
  - getLowSequence
```
public int getLowSequence()
```
    Returns:
    
    the lowSequence
  - getOutputNeuronCount
```
public int getOutputNeuronCount()
```
    Returns:
    
    the outputNeuronCount
  - getPoints
```
public java.util.List<TemporalPoint> getPoints()
```
    Returns:
    
    The temporal points.
  - getPredictWindowSize
```
public int getPredictWindowSize()
```
    Returns:
    
    the predictWindowSize
  - getSequenceFromDate
```
public int getSequenceFromDate(java.util.Date when)
```
    Create a sequence number from a time. The first date will be zero, and subsequent dates will be increased according to the grandularity specified.
    
    Parameters:
    
    when - The date to generate the sequence number for.
    
    Returns:
    
    A sequence number.
  - getSequenceGrandularity
```
public TimeUnit getSequenceGrandularity()
```
    Returns:
    
    the sequenceGrandularity
  - getStartingPoint
```
public java.util.Date getStartingPoint()
```
    Returns:
    
    the startingPoint
  - isPointInRange
```
public boolean isPointInRange(TemporalPoint point)
```
    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.
    
    Parameters:
    
    point - The point to consider.
    
    Returns:
    
    True if the point is within the range.
  - setDesiredSetSize
```
public void setDesiredSetSize(int desiredSetSize)
```
    Parameters:
    
    desiredSetSize - the desiredSetSize to set
  - setHighSequence
```
public void setHighSequence(int highSequence)
```
    Parameters:
    
    highSequence - the highSequence to set
  - setInputWindowSize
```
public void setInputWindowSize(int inputWindowSize)
```
    Parameters:
    
    inputWindowSize - the inputWindowSize to set
  - setLowSequence
```
public void setLowSequence(int lowSequence)
```
    Parameters:
    
    lowSequence - the lowSequence to set
  - setPredictWindowSize
```
public void setPredictWindowSize(int predictWindowSize)
```
    Parameters:
    
    predictWindowSize - the predictWindowSize to set
  - setSequenceGrandularity
```
public void setSequenceGrandularity(TimeUnit sequenceGrandularity)
```
    Parameters:
    
    sequenceGrandularity - the sequenceGrandularity to set
  - setStartingPoint
```
public void setStartingPoint(java.util.Date startingPoint)
```
    Parameters:
    
    startingPoint - the startingPoint to set
  - sortPoints
```
public void sortPoints()
```
    Sort the points.

Class TemporalMLDataSet

Nested Class Summary

Nested classes/interfaces inherited from class org.encog.ml.data.basic.BasicMLDataSet

Field Summary

Constructor Summary

Method Summary

Methods inherited from class org.encog.ml.data.basic.BasicMLDataSet

Methods inherited from class java.lang.Object

Methods inherited from interface org.encog.ml.data.MLDataSet

Methods inherited from interface java.lang.Iterable

Field Detail

ADD_NOT_SUPPORTED

Constructor Detail

TemporalMLDataSet

Method Detail

add

add

add

addDescription

calculateActualSetSize

calculateNeuronCounts

calculatePointsInRange

calculateStartIndex

clear

createPoint

createPoint

generate

generateInputNeuralData

generateOutputNeuralData

getDescriptions

getDesiredSetSize

getHighSequence

getInputNeuronCount

getInputWindowSize

getLowSequence

getOutputNeuronCount

getPoints

getPredictWindowSize

getSequenceFromDate

getSequenceGrandularity

getStartingPoint

isPointInRange

setDesiredSetSize

setHighSequence

setInputWindowSize

setLowSequence

setPredictWindowSize

setSequenceGrandularity

setStartingPoint

sortPoints