org.encog.ml.data.versatile

Class MatrixMLDataSet

java.lang.Object

org.encog.ml.data.versatile.MatrixMLDataSet

All Implemented Interfaces:

java.lang.Iterable<MLDataPair>, MLDataSet

Direct Known Subclasses:

VersatileMLDataSet

public class MatrixMLDataSet
extends java.lang.Object
implements MLDataSet

The MatrixMLDataSet can use a large 2D matrix of doubles to internally hold data. It supports several advanced features such as the ability to mask and time-box. Masking allows several datasets to use the same backing array, however use different parts. Time boxing allows time-series data to be represented for prediction. The following shows how data is laid out for different lag and lead settings. Lag 0; Lead 0 [10 rows] 1→1 2→2 3→3 4→4 5→5 6→6 7→7 8→8 9→9 10→10 Lag 0; Lead 1 [9 rows] 1→2 2→3 3→4 4→5 5→6 6→7 7→8 8→9 9→10 Lag 1; Lead 0 [9 rows, not useful] 1,2→1 2,3→2 3,4→3 4,5→4 5,6→5 6,7→6 7,8→7 8,9→8 9,10→9 Lag 1; Lead 1 [8 rows] 1,2→3 2,3→4 3,4→5 4,5→6 5,6→7 6,7→8 7,8→9 8,9→10 Lag 1; Lead 2 [7 rows] 1,2→3,4 2,3→4,5 3,4→5,6 4,5→6,7 5,6→7,8 6,7→8,9 7,8→9,10 Lag 2; Lead 1 [7 rows] 1,2,3→4 2,3,4→5 3,4,5→6 4,5,6→7 5,6,7→8 6,7,8→9 7,8,9→10

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	MatrixMLDataSet.MatrixMLDataSetIterator An iterator to be used with the MatrixMLDataSet.

Constructor Summary

Constructors

Constructor and Description
MatrixMLDataSet() The default constructor.
MatrixMLDataSet(double[][] theData, int theCalculatedInputSize, int theCalculatedIdealSize) Construct the dataset with no mask.
MatrixMLDataSet(double[][] theData, int inputCount, int idealCount, int[] theMask) Construct the dataset from a 2D double array..
MatrixMLDataSet(MatrixMLDataSet data, int[] mask) Construct the dataset from another matrix dataset.

Method Summary

Modifier and Type	Method and Description
void	add(MLData data1) Add a object to the dataset.
void	add(MLData inputData, MLData idealData) Add a set of input and ideal data to the dataset.
void	add(MLDataPair inputData) Add a an object to the dataset.
void	close() Close this datasource and release any resources obtained by it, including any iterators created.
MLDataPair	get(int index)
int	getCalculatedIdealSize()
int	getCalculatedInputSize()
double[][]	getData()
int	getIdealSize()
int	getInputSize()
int	getLagWindowSize()
int	getLeadWindowSize()
int[]	getMask()
void	getRecord(long index, MLDataPair pair) Read an individual record, specified by index, in random order.
long	getRecordCount() Determine the total number of records in the set.
boolean	isSupervised()
java.util.Iterator<MLDataPair>	iterator()
MLDataSet	openAdditional() Opens an additional instance of this dataset.
void	setCalculatedIdealSize(int calculatedIdealSize)
void	setCalculatedInputSize(int calculatedInputSize)
void	setData(double[][] data)
void	setLagWindowSize(int lagWindowSize)
void	setLeadWindowSize(int leadWindowSize)
int	size()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface java.lang.Iterable

forEach, spliterator

Constructor Detail

MatrixMLDataSet

public MatrixMLDataSet()

The default constructor.

MatrixMLDataSet

public MatrixMLDataSet(double[][] theData,
                       int theCalculatedInputSize,
                       int theCalculatedIdealSize)

Construct the dataset with no mask.

Parameters:

theData - The backing array.

theCalculatedInputSize - The input size.

theCalculatedIdealSize - The ideal size.

MatrixMLDataSet

public MatrixMLDataSet(double[][] theData,
                       int inputCount,
                       int idealCount,
                       int[] theMask)

Construct the dataset from a 2D double array..

Parameters:

theData - The data.

inputCount - The input count.

idealCount - The ideal count.

theMask - The mask.

MatrixMLDataSet

public MatrixMLDataSet(MatrixMLDataSet data,
                       int[] mask)

Construct the dataset from another matrix dataset.

Parameters:

data - The data.

mask - The mask.

Method Detail

getMask

public int[] getMask()

Returns:

The mask.

iterator

public java.util.Iterator<MLDataPair> iterator()

Specified by:

iterator in interface java.lang.Iterable<MLDataPair>

getIdealSize

public int getIdealSize()

Specified by:

getIdealSize in interface MLDataSet

Returns:

The size of the ideal data.

getInputSize

public int getInputSize()

Specified by:

getInputSize in interface MLDataSet

Returns:

The size of the input data.

isSupervised

public boolean isSupervised()

Specified by:

isSupervised in interface MLDataSet

Returns:

True if this is a supervised training set.

getRecordCount

public long getRecordCount()

Determine the total number of records in the set.

Specified by:

getRecordCount in interface MLDataSet

Returns:

The total number of records in the set.

getRecord

public void getRecord(long index,
                      MLDataPair pair)

Read an individual record, specified by index, in random order.

Specified by:

getRecord in interface MLDataSet

Parameters:

index - The index to read.

pair - The pair that the record will be copied into.

openAdditional

public MLDataSet openAdditional()

Opens an additional instance of this dataset.

Specified by:

openAdditional in interface MLDataSet

Returns:

The new instance.

add

public void add(MLData data1)

Add a object to the dataset. This is used with unsupervised training, as no ideal output is provided. Note: not all implemenations support the add methods.

Specified by:

add in interface MLDataSet

Parameters:

data1 - The data item to be added.

add

public void add(MLData inputData,
                MLData idealData)

Add a set of input and ideal data to the dataset. This is used with supervised training, as ideal output is provided. Note: not all implementations support the add methods.

Specified by:

add in interface MLDataSet

Parameters:

inputData - Input data.

idealData - Ideal data.

add

public void add(MLDataPair inputData)

Add a an object to the dataset. This is used with unsupervised training, as no ideal output is provided. Note: not all implementations support the add methods.

Specified by:

add in interface MLDataSet

Parameters:

inputData - A MLDataPair object that contains both input and ideal data.

close

public void close()

Close this datasource and release any resources obtained by it, including any iterators created.

Specified by:

close in interface MLDataSet

size

public int size()

Specified by:

size in interface MLDataSet

get

public MLDataPair get(int index)

Specified by:

get in interface MLDataSet

getCalculatedInputSize

public int getCalculatedInputSize()

Returns:

the calculatedInputSize

setCalculatedInputSize

public void setCalculatedInputSize(int calculatedInputSize)

Parameters:

calculatedInputSize - the calculatedInputSize to set

getCalculatedIdealSize

public int getCalculatedIdealSize()

Returns:

the calculatedIdealSize

setCalculatedIdealSize

public void setCalculatedIdealSize(int calculatedIdealSize)

Parameters:

calculatedIdealSize - the calculatedIdealSize to set

getData

public double[][] getData()

Returns:

the data

setData

public void setData(double[][] data)

Parameters:

data - the data to set

getLagWindowSize

public int getLagWindowSize()

Returns:

the lagWindowSize

setLagWindowSize

public void setLagWindowSize(int lagWindowSize)

Parameters:

lagWindowSize - the lagWindowSize to set

getLeadWindowSize

public int getLeadWindowSize()

Returns:

the leadWindowSize

setLeadWindowSize

public void setLeadWindowSize(int leadWindowSize)

Parameters:

leadWindowSize - the leadWindowSize to set