it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive

Class LinearPassiveAggressiveClassification

java.lang.Object

it.uniroma2.sag.kelp.learningalgorithm.PassiveAggressive

it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive.PassiveAggressiveClassification

it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive.LinearPassiveAggressiveClassification

All Implemented Interfaces:

BinaryLearningAlgorithm, ClassificationLearningAlgorithm, LearningAlgorithm, LinearMethod, OnlineLearningAlgorithm

public class LinearPassiveAggressiveClassification
extends PassiveAggressiveClassification
implements LinearMethod

Online Passive-Aggressive Learning Algorithm for classification tasks (linear version) . Every time an example is misclassified it is added the the current hyperplane, with the weight that solves the passive aggressive minimization problem reference:

[CrammerJLMR2006] Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz and Yoram Singer Online Passive-Aggressive Algorithms. Journal of Machine Learning Research (2006)

The standard algorithm is modified, including the fairness extention from

[FiliceECIR2014] S. Filice, G. Castellucci, D. Croce, and R. Basili. Effective Kernelized Online Learning in Language Processing Tasks. In collection of Advances in Information Retrieval, pp. 347–358, Springer International Publishing, 2014.

Author:

Simone Filice

Nested Class Summary

Nested classes/interfaces inherited from class it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive.PassiveAggressiveClassification

PassiveAggressiveClassification.Loss

Nested classes/interfaces inherited from class it.uniroma2.sag.kelp.learningalgorithm.PassiveAggressive

PassiveAggressive.Policy

Field Summary

Fields inherited from class it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive.PassiveAggressiveClassification

classifier, cp, fairness, loss

Fields inherited from class it.uniroma2.sag.kelp.learningalgorithm.PassiveAggressive

c, label, policy

Constructor Summary

Constructors

Constructor and Description
LinearPassiveAggressiveClassification()
LinearPassiveAggressiveClassification(float cp, float cn, PassiveAggressiveClassification.Loss loss, PassiveAggressive.Policy policy, String representation, Label label)

Method Summary

Methods

Modifier and Type	Method and Description
LinearPassiveAggressiveClassification	duplicate() Creates a new instance of the LearningAlgorithm initialized with the same parameters of the learningAlgorithm to be duplicated.
BinaryLinearClassifier	getPredictionFunction() Returns the classifier learned during the training process
String	getRepresentation() Returns the representation this learning algorithm exploits
void	setPredictionFunction(PredictionFunction predictionFunction) Sets the predictionFunction learned during the training process.
void	setRepresentation(String representation) Sets the representation this learning algorithm will exploit

Methods inherited from class it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive.PassiveAggressiveClassification

getC, getCn, getCp, getLoss, isFairness, learn, learn, setC, setCn, setCp, setFairness, setLoss

Methods inherited from class it.uniroma2.sag.kelp.learningalgorithm.PassiveAggressive

computeWeight, getLabel, getLabels, getPolicy, reset, setLabel, setLabels, setPolicy

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.learningalgorithm.LearningAlgorithm

getLabels, reset, setLabels

Constructor Detail

LinearPassiveAggressiveClassification

public LinearPassiveAggressiveClassification()

LinearPassiveAggressiveClassification

public LinearPassiveAggressiveClassification(float cp,
                                     float cn,
                                     PassiveAggressiveClassification.Loss loss,
                                     PassiveAggressive.Policy policy,
                                     String representation,
                                     Label label)

Method Detail

getRepresentation

public String getRepresentation()

Description copied from interface: LinearMethod

Returns the representation this learning algorithm exploits

Specified by:

getRepresentation in interface LinearMethod

Returns:

the representation

setRepresentation

public void setRepresentation(String representation)

Description copied from interface: LinearMethod

Sets the representation this learning algorithm will exploit

Specified by:

setRepresentation in interface LinearMethod

Parameters:

representation - the representation to set

duplicate

public LinearPassiveAggressiveClassification duplicate()

Description copied from interface: LearningAlgorithm

Creates a new instance of the LearningAlgorithm initialized with the same parameters of the learningAlgorithm to be duplicated. A shallow copy of the learning parameters is performed, while the state parameters are initialized to their default value. The labels are not initialized neither copied

Specified by:

duplicate in interface LearningAlgorithm

getPredictionFunction

public BinaryLinearClassifier getPredictionFunction()

Description copied from interface: ClassificationLearningAlgorithm

Returns the classifier learned during the training process

Specified by:

getPredictionFunction in interface ClassificationLearningAlgorithm

Specified by:

getPredictionFunction in interface LearningAlgorithm

Overrides:

getPredictionFunction in class PassiveAggressiveClassification

Returns:

the predictionFunction learned during the training process

setPredictionFunction

public void setPredictionFunction(PredictionFunction predictionFunction)

Description copied from interface: LearningAlgorithm

Sets the predictionFunction learned during the training process. It can be used to change the default prediction function, or to set an already trained one.

Specified by:

setPredictionFunction in interface LearningAlgorithm