it.uniroma2.sag.kelp.predictionfunction.classifier

Class BinaryClassifier

java.lang.Object

it.uniroma2.sag.kelp.predictionfunction.classifier.BinaryClassifier

All Implemented Interfaces:

Classifier, PredictionFunction

Direct Known Subclasses:

BinaryKernelMachineClassifier, BinaryLinearClassifier

public abstract class BinaryClassifier
extends Object
implements Classifier

It is a generic binary classification function that can be learned with a machine learning algorithm It learns a binary concept. It considers positive examples the ones associated to a specific Label and treats like negative examples all the others

Author:

Simone Filice

Field Summary

Fields

Modifier and Type	Field and Description
protected Label	positiveClass

Constructor Summary

Constructors

Constructor and Description
BinaryClassifier()

Method Summary

Methods

Modifier and Type	Method and Description
Label	getLabel()
List<Label>	getLabels() Returns the labels representing the concept to be predicted.
abstract BinaryModel	getModel() Returns the model
abstract BinaryMarginClassifierOutput	predict(Example example)
void	setLabel(Label label)
void	setLabels(List<Label> labels) Sets the labels representing the concept to be predicted.

Methods inherited from class java.lang.Object

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

Methods inherited from interface it.uniroma2.sag.kelp.predictionfunction.PredictionFunction

reset, setModel

Field Detail

positiveClass

protected Label positiveClass

Constructor Detail

BinaryClassifier

public BinaryClassifier()

Method Detail

setLabels

public void setLabels(List<Label> labels)

Description copied from interface: PredictionFunction

Sets the labels representing the concept to be predicted.

Specified by:

setLabels in interface PredictionFunction

Parameters:

positiveClass - the label associated to the positive class, i.e. the list must contain a sigle entry

getLabels

public List<Label> getLabels()

Description copied from interface: PredictionFunction

Returns the labels representing the concept to be predicted.

Specified by:

getLabels in interface PredictionFunction

Returns:

the label associated to the positive class, i.e. the output list contains a single entry

getLabel

public Label getLabel()

Returns:

the label associated to the positive class

setLabel

public void setLabel(Label label)

Parameters:

positiveClass - the label associated to the positive class

predict

public abstract BinaryMarginClassifierOutput predict(Example example)

Specified by:

predict in interface Classifier

Specified by:

predict in interface PredictionFunction

getModel

public abstract BinaryModel getModel()

Description copied from interface: PredictionFunction

Returns the model

Specified by:

getModel in interface PredictionFunction

Returns:

the model