Package deepnetts.data

Class TabularDataSet<T extends MLDataItem>

java.lang.Object

javax.visrec.ml.data.BasicDataSet<T>

deepnetts.data.TabularDataSet<T>

Type Parameters:

T - Type of elements in this data set.

All Implemented Interfaces:

Iterable<T>, javax.visrec.ml.data.DataSet<T>

Direct Known Subclasses:

ImageSet

public class TabularDataSet<T extends MLDataItem>
extends javax.visrec.ml.data.BasicDataSet<T>

Basic data set with tabular data. Used for training neural networks in Deep Netts.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	TabularDataSet.Item	Represents a basic data set item (single row) with input tensor and target vector in a data set.

Constructor Summary

Constructors

Constructor	Description
TabularDataSet(int numInputs, int numOutputs)	Create a new instance of BasicDataSet with specified size of input and output.

Method Summary

Modifier and Type	Method	Description
int[]	countMissingValues()
int	countMissingValues(int colIdx)
String[]	getColumnNames()
int	getNumInputs()
int	getNumOutputs()
String[]	getTargetColumnsNames()
boolean[]	hasMissingValues()
boolean	hasMissingValues(int colIdx)
void	setColumnNames(String[] columnNames)
void	shuffle()	Shuffles the data set items using the default random generator.
void	shuffle(int seed)	Shuffles data set items using java random generator initializes with specified seed
javax.visrec.ml.data.DataSet[]	split(double... parts)	Splits data set into several parts specified by the input parameter partSizes.
javax.visrec.ml.data.DataSet[]	split(int parts)	Split data set into specified number of part of equal sizes.
TrainTestSplit	trainTestSplit(double splitRatio)

Methods inherited from class javax.visrec.ml.data.BasicDataSet

getColumns, getItems, setAsTargetColumns, setAsTargetColumns, setColumns

Methods inherited from class java.lang.Object

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

Methods inherited from interface javax.visrec.ml.data.DataSet

add, addAll, clear, get, isEmpty, iterator, shuffle, size, split, split, split, stream

Methods inherited from interface java.lang.Iterable

forEach, spliterator

Constructor Details

TabularDataSet

public TabularDataSet(int numInputs,
 int numOutputs)

Create a new instance of BasicDataSet with specified size of input and output.

Parameters:

numInputs - number of input features

numOutputs - number of output features

Method Details

getNumInputs

public int getNumInputs()

getNumOutputs

public int getNumOutputs()

split

public javax.visrec.ml.data.DataSet[] split(int parts)

Split data set into specified number of part of equal sizes. Utility method used during cross-validation Note: this could be default method

Parameters:

parts -

Returns:

trainTestSplit

public TrainTestSplit trainTestSplit(double splitRatio)

split

public javax.visrec.ml.data.DataSet[] split(double... parts)

Splits data set into several parts specified by the input parameter partSizes. Values of partSizes parameter represent the sizes of data set parts that will be returned. Part sizes are decimal values that represent percents, cannot be negative or zero, and their sum must be 1

Specified by:

split in interface javax.visrec.ml.data.DataSet<T extends MLDataItem>

Overrides:

split in class javax.visrec.ml.data.BasicDataSet<T extends MLDataItem>

Parameters:

parts - sizes of the parts in percents

Returns:

parts of the data set of specified size

shuffle

public void shuffle()

Shuffles the data set items using the default random generator. Default rng can be initialized independently

shuffle

public void shuffle(int seed)

Shuffles data set items using java random generator initializes with specified seed

Parameters:

seed - a seed number to initialize random generator

See Also:

• Random

getColumnNames

public String[] getColumnNames()

Overrides:

getColumnNames in class javax.visrec.ml.data.BasicDataSet<T extends MLDataItem>

setColumnNames

public void setColumnNames(String[] columnNames)

Overrides:

setColumnNames in class javax.visrec.ml.data.BasicDataSet<T extends MLDataItem>

getTargetColumnsNames

public String[] getTargetColumnsNames()

Specified by:

getTargetColumnsNames in interface javax.visrec.ml.data.DataSet<T extends MLDataItem>

Overrides:

getTargetColumnsNames in class javax.visrec.ml.data.BasicDataSet<T extends MLDataItem>

hasMissingValues

public boolean hasMissingValues(int colIdx)

hasMissingValues

public boolean[] hasMissingValues()

countMissingValues

public int countMissingValues(int colIdx)

countMissingValues

public int[] countMissingValues()