Example (kelp-full 1.1.1 API)

java.lang.Object
- it.uniroma2.sag.kelp.data.example.Example

All Implemented Interfaces:

Serializable

Direct Known Subclasses:

SimpleExample
```
public abstract class Example
extends Object
implements Serializable
```
It is the instance of an example in the Machine Learning context. An Example consists of one or more representation of the same object and zero (unsupervised learning) or more classificationLabels (supervised learning. Single or multitask learning)

Author:

Simone Filice

See Also:
Serialized Form

Constructor Summary

Constructors
Constructor and Description

Example()
Initializes an empty example (0 classificationLabels and 0 regression values)

Constructors
Constructor and Description
`Example()` Initializes an empty example (0 classificationLabels and 0 regression values)

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`addLabel(Label label)` Adds a label to the example
`abstract void`	`addRepresentation(String representationName, Representation representation)` Adds a representation to this example
`Example`	`clone()`
`boolean`	`equals(Object example)`
`HashSet<Label>`	`getClassificationLabels()`
`long`	`getId()` Returns a unique identifier of the example.
`Label[]`	`getLabels()` Returns the classification classificationLabels of this example
`int`	`getNumberOfClassificationLabels()` Returns the number of classification classificationLabels whose this instance is a positive example
`int`	`getNumberOfRegressionLabels()` Returns the number of regression classificationLabels
`abstract int`	`getNumberOfRepresentations()` Returns the number of representations in which this example is modeled
`NumericLabel[]`	`getRegressionLabels()` Returns the classificationLabels of this example
`Float`	`getRegressionValue(Label property)` Returns the numeric value associated to a label
`ArrayList<NumericLabel>`	`getRegressionValues()`
`abstract Representation`	`getRepresentation(String representationName)` Returns the representation corresponding to `representationName`
`abstract Map<String,Representation>`	`getRepresentations()` Returns the example representations
`protected String`	`getTextualLabelPart()`
`abstract Vector`	`getZeroVector(String representationIdentifier)`
`boolean`	`isExampleOf(Label label)` Asserts whether this is a positive example for the input label or not
`abstract void`	`manipulate(Manipulator manipulator)` Manipulate this example accordingly to the provided `manipulator`
`void`	`setClassificationLabels(HashSet<Label> labels)`
`void`	`setLabels(Label[] labels)` Sets the example classificationLabels
`void`	`setRegressionValues(ArrayList<NumericLabel> regressionValues)`
`abstract void`	`setRepresentations(HashMap<String,Representation> representations)` Sets the example representations

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

- Constructor Detail
  - Example
```
public Example()
```
    Initializes an empty example (0 classificationLabels and 0 regression values)
- Method Detail
  - getId
```
public long getId()
```
    Returns a unique identifier of the example. The Unique identifier is a number univocally and statically assigned to the example during its initialization.
    Note: initializing two identical examples will make them having two different IDs
    
    Returns:
    the example ID
  - setLabels
```
public void setLabels(Label[] labels)
```
    Sets the example classificationLabels
    
    Parameters:
    classificationLabels - of which this instance is a positive example
  - getLabels
```
public Label[] getLabels()
```
    Returns the classification classificationLabels of this example
    
    Returns:
    the classification classificationLabels of this example
  - getRegressionLabels
```
public NumericLabel[] getRegressionLabels()
```
    Returns the classificationLabels of this example
    
    Returns:
    the classificationLabels of this example
  - addLabel
```
public void addLabel(Label label)
```
    Adds a label to the example
    
    Parameters:
    label -
  - getNumberOfClassificationLabels
```
public int getNumberOfClassificationLabels()
```
    Returns the number of classification classificationLabels whose this instance is a positive example
    
    Returns:
    the number of classificationLabels whose this instance is a positive example
  - getNumberOfRegressionLabels
```
public int getNumberOfRegressionLabels()
```
    Returns the number of regression classificationLabels
    
    Returns:
    the number of regression classificationLabels
  - isExampleOf
```
public boolean isExampleOf(Label label)
```
    Asserts whether this is a positive example for the input label or not
    
    Parameters:
    label -
    
    Returns:
    true if this is a positive example of the class label, false otherwise
  - getRegressionValue
```
public Float getRegressionValue(Label property)
```
    Returns the numeric value associated to a label
    
    Parameters:
    propertyName - the regression label identifier
    
    Returns:
    the numeric value associated to the label identified by propertyName or null if that label is not a NumericLabel or this example does not contain that label
  - getClassificationLabels
```
public HashSet<Label> getClassificationLabels()
```
    Returns:
    the classificationLabels
  - setClassificationLabels
```
public void setClassificationLabels(HashSet<Label> labels)
```
    Parameters:
    classificationLabels - the classificationLabels to set
  - getRegressionValues
```
public ArrayList<NumericLabel> getRegressionValues()
```
    Returns:
    the regressionValues
  - setRegressionValues
```
public void setRegressionValues(ArrayList<NumericLabel> regressionValues)
```
    Parameters:
    regressionValues - the regressionValues to set
  - equals
```
public boolean equals(Object example)
```
    Overrides:
    
    equals in class Object
  - clone
```
public Example clone()
```
    Overrides:
    
    clone in class Object
  - getTextualLabelPart
```
protected String getTextualLabelPart()
```
  - setRepresentations
```
public abstract void setRepresentations(HashMap<String,Representation> representations)
```
    Sets the example representations
    
    Parameters:
    representations - to associate to this example
  - getRepresentations
```
public abstract Map<String,Representation> getRepresentations()
```
    Returns the example representations
    
    Returns:
    the representations of this example
  - addRepresentation
```
public abstract void addRepresentation(String representationName,
                     Representation representation)
```
    Adds a representation to this example
    
    Parameters:
    representationName - the identifier of the representation to be added
    representation - the representation to be added
  - getNumberOfRepresentations
```
public abstract int getNumberOfRepresentations()
```
    Returns the number of representations in which this example is modeled
    
    Returns:
    the number of representations
  - getRepresentation
```
public abstract Representation getRepresentation(String representationName)
```
    Returns the representation corresponding to representationName
    
    Parameters:
    representationName - it is a representation identifier
    
    Returns:
    the representation corresponding to representationName
  - getZeroVector
```
public abstract Vector getZeroVector(String representationIdentifier)
```
  - manipulate
```
public abstract void manipulate(Manipulator manipulator)
```
    Manipulate this example accordingly to the provided manipulator
    
    Parameters:
    manipulator - the manipulator

Class Example

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Example

Method Detail

getId

setLabels

getLabels

getRegressionLabels

addLabel

getNumberOfClassificationLabels

getNumberOfRegressionLabels

isExampleOf

getRegressionValue

getClassificationLabels

setClassificationLabels

getRegressionValues

setRegressionValues

equals

clone

getTextualLabelPart

setRepresentations

getRepresentations

addRepresentation

getNumberOfRepresentations

getRepresentation

getZeroVector

manipulate