DataSet (javax.visrec:visrec-api 1.0.0 API)

Type Parameters:

E - type of data set elements

All Superinterfaces:

Iterable<E>

All Known Implementing Classes:

BasicDataSet
```
public interface DataSet<E>
extends Iterable<E>
```
Generic interface for all data sets for machine learning, independent of type of elements.

Since:

1.0

Author:

Zoran Sevarac

Nested Class Summary

Nested Classes
Modifier and Type Interface and Description

static class DataSet.Column

static class DataSet.Type

Nested Classes
Modifier and Type	Interface and Description
`static class`	`DataSet.Column`
`static class`	`DataSet.Type`

Method Summary

All Methods Instance Methods Abstract Methods Default Methods
Modifier and Type	Method and Description
`default DataSet<E>`	`add(E item)` Adds an element to this data set.
`default DataSet<E>`	`addAll(DataSet<E> dataSet)` Add an existing `DataSet` to the current `DataSet`
`default void`	`clear()` Clear items of the `DataSet`
`default E`	`get(int idx)` Get an item from the `DataSet`
`String[]`	`getColumnNames()`
`List<E>`	`getItems()` Get a collection of the items in the `DataSet`
`String[]`	`getTargetNames()` Get labels of target/output columns.
`default boolean`	`isEmpty()` Determines whether the `DataSet` is empty or not.
`default Iterator<E>`	`iterator()`
`void`	`setColumnNames(String[] columnNames)`
`default void`	`shuffle()` Shuffles the data set.
`default void`	`shuffle(Random rnd)` Shuffles the data set using the specified random number generator.
`default int`	`size()` Get the number of elements in `DataSet`
`DataSet<E>[]`	`split(double... parts)` Split data set into parts of specified sizes
`default DataSet<E>[]`	`split(double part)` Split data set in two parts, one with size of specified percentage, and other with rest of the data set
`default DataSet<E>[]`	`split(int numParts)` Split dataset into specified number of equally sized parts.
`default DataSet<E>[]`	`split(int numParts, Random rnd)` Split dataset into specified number of equally sized parts, using specified random generator.
`default DataSet<E>[]`	`split(Random rnd, double... parts)` Split data set into parts of specified sizes using specified random generator

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

- Method Detail
  - getItems
```
List<E> getItems()
```
    Get a collection of the items in the DataSet
    
    Returns:
    
    Collection
  - add
```
default DataSet<E> add(E item)
```
    Adds an element to this data set.
    
    Parameters:
    
    item - data set item to add to the data set
    
    Returns:
    
    current instance of DataSet
  - addAll
```
default DataSet<E> addAll(DataSet<E> dataSet)
```
    Add an existing DataSet to the current DataSet
    
    Parameters:
    
    dataSet - existing DataSet
    
    Returns:
    
    current instance of DataSet
  - get
```
default E get(int idx)
```
    Get an item from the DataSet
    
    Parameters:
    
    idx - index as int which corresponds with the index of the DataSet
    
    Returns:
    
    item from the DataSet
  - clear
```
default void clear()
```
    Clear items of the DataSet
  - isEmpty
```
default boolean isEmpty()
```
    Determines whether the DataSet is empty or not.
    
    Returns:
    
    true if the DataSet is empty, otherwise false
  - size
```
default int size()
```
    Get the number of elements in DataSet
    
    Returns:
    
    size in int
  - iterator
```
default Iterator<E> iterator()
```
    Specified by:
    
    iterator in interface Iterable<E>
  - split
```
default DataSet<E>[] split(int numParts)
```
    Split dataset into specified number of equally sized parts.
    
    Parameters:
    
    numParts - number of parts to be returned
    
    Returns:
    
    multiple DataSet in an array.
  - split
```
default DataSet<E>[] split(int numParts,
                           Random rnd)
```
    Split dataset into specified number of equally sized parts, using specified random generator.
    
    Parameters:
    
    numParts - number of parts/subsets to return
    
    rnd - random number generator
    
    Returns:
    
    multiple DataSet in an array.
  - split
```
default DataSet<E>[] split(double part)
```
    Split data set in two parts, one with size of specified percentage, and other with rest of the data set
    
    Parameters:
    
    part - specified percentage of the first DataSet
    
    Returns:
    
    multiple DataSet in an array.
  - split
```
DataSet<E>[] split(double... parts)
```
    Split data set into parts of specified sizes
    
    Parameters:
    
    parts - specific sizes of DataSet
    
    Returns:
    
    array of DataSet
  - split
```
default DataSet<E>[] split(Random rnd,
                           double... parts)
```
    Split data set into parts of specified sizes using specified random generator
    
    Parameters:
    
    rnd - random generator
    
    parts - specific sizes of DataSet
    
    Returns:
    
    array of DataSet
  - shuffle
```
default void shuffle()
```
    Shuffles the data set.
  - shuffle
```
default void shuffle(Random rnd)
```
    Shuffles the data set using the specified random number generator.
    
    Parameters:
    
    rnd - random generator
  - getTargetNames
```
String[] getTargetNames()
```
    Get labels of target/output columns.
    
    Returns:
    
    array with labels of target/output columns
  - setColumnNames
```
void setColumnNames(String[] columnNames)
```
  - getColumnNames
```
String[] getColumnNames()
```

Interface DataSet<E>

Nested Class Summary

Method Summary

Methods inherited from interface java.lang.Iterable

Method Detail

getItems

add

addAll

get

clear

isEmpty

size

iterator

split

split

split

split

split

shuffle

shuffle

getTargetNames

setColumnNames

getColumnNames