Uses of Interface
it.uniroma2.sag.kelp.learningalgorithm.LearningAlgorithm

Packages that use LearningAlgorithm

Package	Description
it.uniroma2.sag.kelp.examples.demo.rcv1
it.uniroma2.sag.kelp.learningalgorithm
it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm
it.uniroma2.sag.kelp.learningalgorithm.classification
it.uniroma2.sag.kelp.learningalgorithm.classification.dcd
it.uniroma2.sag.kelp.learningalgorithm.classification.hmm
it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear
it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm
it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver
it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification
it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive
it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos
it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron
it.uniroma2.sag.kelp.learningalgorithm.classification.scw
it.uniroma2.sag.kelp.learningalgorithm.regression
it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear
it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm
it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive
it.uniroma2.sag.kelp.utils

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.examples.demo.rcv1

Methods in it.uniroma2.sag.kelp.examples.demo.rcv1 that return LearningAlgorithm

Modifier and Type	Method and Description
static LearningAlgorithm	RCV1BinaryTextCategorizationLibLinearExperimentUtils.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
static LearningAlgorithm	RCV1BinaryTextCategorizationPAExperimentUtils.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
protected LearningAlgorithm	RCV1BinaryTextCategorizationDCD.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
static LearningAlgorithm	RCV1BinaryTextCategorizationSCWExperimentUtils.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
static LearningAlgorithm	RCV1BinaryTextCategorizationDCDExperimentUtils.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
protected LearningAlgorithm	RCV1BinaryTextCategorizationPegasos.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
protected LearningAlgorithm	RCV1BinaryTextCategorizationLibLinear.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
protected LearningAlgorithm	RCV1BinaryTextCategorizationSCW.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
protected abstract LearningAlgorithm	RCV1BinaryTextCategorization.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
protected LearningAlgorithm	RCV1BinaryTextCategorizationPA.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)
static LearningAlgorithm	RCV1BinaryTextCategorizationPegasosExperimentUtils.getLearningAlgorithm(float param, String representation, StringLabel positiveLabel)

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm

Subinterfaces of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm

Modifier and Type	Interface and Description
interface	BinaryLearningAlgorithm It is a learning algorithm that has to learn a concept associated to a single label.
interface	EnsembleLearningAlgorithm It is an ensemble method that operates combining various learning algorithms
interface	MetaLearningAlgorithm It is a meta algorithm that operates modifying exploiting another learning algorithm
interface	OnlineLearningAlgorithm It is a Machine Learning algorithm which allows an incremental learning strategy, exploiting a single Example at a time

Classes in it.uniroma2.sag.kelp.learningalgorithm that implement LearningAlgorithm

Modifier and Type	Class and Description
class	MultiEpochLearning It is a meta learning algorithms for online learning methods.
class	PassiveAggressive It is an online learning algorithms that implements the Passive Aggressive algorithms described in [Crammer, JMLR2006] K.

Methods in it.uniroma2.sag.kelp.learningalgorithm that return LearningAlgorithm

Modifier and Type	Method and Description
LearningAlgorithm	LearningAlgorithm.duplicate() Creates a new instance of the LearningAlgorithm initialized with the same parameters of the learningAlgorithm to be duplicated.
LearningAlgorithm	MultiEpochLearning.getBaseAlgorithm()
LearningAlgorithm	MetaLearningAlgorithm.getBaseAlgorithm() Returns the base algorithm this meta algorithm is based on

Methods in it.uniroma2.sag.kelp.learningalgorithm that return types with arguments of type LearningAlgorithm

Modifier and Type	Method and Description
List<LearningAlgorithm>	EnsembleLearningAlgorithm.getToCombine() Returns a list of the learning algorithm this ensemble method is combining

Methods in it.uniroma2.sag.kelp.learningalgorithm with parameters of type LearningAlgorithm

Modifier and Type	Method and Description
void	MultiEpochLearning.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
void	MetaLearningAlgorithm.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm with type arguments of type LearningAlgorithm

Modifier and Type	Method and Description
void	EnsembleLearningAlgorithm.setToCombine(List<LearningAlgorithm> toCombine)

Constructors in it.uniroma2.sag.kelp.learningalgorithm with parameters of type LearningAlgorithm

Constructor and Description
MultiEpochLearning(int epochs, LearningAlgorithm baseAlgorithm)
MultiEpochLearning(int epochs, LearningAlgorithm baseAlgorithm, List<Label> labels)

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm

Classes in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm that implement LearningAlgorithm

Modifier and Type	Class and Description
class	BudgetedLearningAlgorithm It is binary kernel-based online learning method that binds the number of support vector to a fix number (i.e.
class	RandomizedBudgetPerceptron It is a variation of the Randomized Budget Perceptron proposed in
class	Stoptron It is a variation of the Stoptron proposed in

Methods in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm with parameters of type LearningAlgorithm

Modifier and Type	Method and Description
void	Stoptron.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
void	RandomizedBudgetPerceptron.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification

Subinterfaces of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification

Modifier and Type	Interface and Description
interface	ClassificationLearningAlgorithm It is a generic Machine Learning algorithm for Classification tasks

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.dcd

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.dcd that implement LearningAlgorithm

Modifier and Type	Class and Description
class	DCDLearningAlgorithm Implements Dual Coordinate Descent (DCD) training algorithms for a Linear L1 or L2 Support Vector Machine for binary classification.

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm that implement LearningAlgorithm

Modifier and Type	Class and Description
class	SequenceClassificationKernelBasedLearningAlgorithm /** This class implements a sequential labeling paradigm.
class	SequenceClassificationLearningAlgorithm This class implements a sequential labeling paradigm.
class	SequenceClassificationLinearLearningAlgorithm This class implements a sequential labeling paradigm.

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm that return LearningAlgorithm

Modifier and Type	Method and Description
LearningAlgorithm	SequenceClassificationLinearLearningAlgorithm.duplicate()
LearningAlgorithm	SequenceClassificationKernelBasedLearningAlgorithm.duplicate()
LearningAlgorithm	SequenceClassificationLinearLearningAlgorithm.getBaseAlgorithm()
LearningAlgorithm	SequenceClassificationKernelBasedLearningAlgorithm.getBaseAlgorithm()
LearningAlgorithm	SequenceClassificationLearningAlgorithm.getBaseLearningAlgorithm()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm with parameters of type LearningAlgorithm

Modifier and Type	Method and Description
void	SequenceClassificationLinearLearningAlgorithm.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
void	SequenceClassificationKernelBasedLearningAlgorithm.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
void	SequenceClassificationLearningAlgorithm.setBaseLearningAlgorithm(LearningAlgorithm baseLearningAlgorithm)

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear that implement LearningAlgorithm

Modifier and Type	Class and Description
class	LibLinearLearningAlgorithm This class implements linear SVMs models trained using a coordinate descent algorithm [Fan et al, 2008].

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm that implement LearningAlgorithm

Modifier and Type	Class and Description
class	BinaryCSvmClassification It implements the C-SVM learning algorithm discussed in [CC Chang & CJ Lin, 2011].
class	BinaryNuSvmClassification It implements the \(\nu\)-SVM learning algorithm discussed in [CC Chang & CJ Lin, 2011].
class	OneClassSvmClassification It implements the One class SVM learning algorithm discussed in [CC Chang & CJ Lin, 2011].

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver that implement LearningAlgorithm

Modifier and Type	Class and Description
class	LibCSvmSolver This class implements the solver of the C-SVM quadratic problem described in [CC Chang & CJ Lin, 2011].
class	LibNuSvmSolver It is the instance of a solution provided the \(\nu\)-SVM solver of the optimization problem.
class	LibSvmSolver This class implements the solver of the SVM quadratic problem described in [CC Chang & CJ Lin, 2011].

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification that implement LearningAlgorithm

Modifier and Type	Class and Description
class	MultiLabelClassificationLearning It is a meta algorithm that operates applying a multi label learning strategy over the base learning algorithm which is intended to be a binary learner.
class	OneVsAllLearning It is a meta algorithm that operates applying a One-Vs-All strategy over the base learning algorithm which is intended to be a binary learner.
class	OneVsOneLearning It is a meta algorithm that operates by applying a One-Vs-One strategy over the base learning algorithm which is intended to be a binary learner.

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification that return LearningAlgorithm

Modifier and Type	Method and Description
LearningAlgorithm	OneVsOneLearning.getBaseAlgorithm() This method will return the base algorithm.
LearningAlgorithm	OneVsAllLearning.getBaseAlgorithm() This method will return the base algorithm.
LearningAlgorithm	MultiLabelClassificationLearning.getBaseAlgorithm() This method will return the base algorithm.

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification with parameters of type LearningAlgorithm

Modifier and Type	Method and Description
void	OneVsOneLearning.setBaseAlgorithm(LearningAlgorithm baseAlgorithm) This method will set the type of the base algorithms to be learned.
void	OneVsAllLearning.setBaseAlgorithm(LearningAlgorithm baseAlgorithm) This method will set the type of the base algorithms to be learned.
void	MultiLabelClassificationLearning.setBaseAlgorithm(LearningAlgorithm baseAlgorithm) This method will set the type of the base algorithms to be learned.

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive that implement LearningAlgorithm

Modifier and Type	Class and Description
class	BudgetedPassiveAggressiveClassification Online Passive-Aggressive on a budget reference: Zhuang Wang and Slobodan Vucetic Online Passive-Aggressive Algorithms on a Budget
class	KernelizedPassiveAggressiveClassification Online Passive-Aggressive Learning Algorithm for classification tasks (Kernel Machine version) .
class	LinearPassiveAggressiveClassification Online Passive-Aggressive Learning Algorithm for classification tasks (linear version) .
class	PassiveAggressiveClassification Online Passive-Aggressive Learning Algorithm for classification tasks.

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive that return LearningAlgorithm

Modifier and Type	Method and Description
LearningAlgorithm	BudgetedPassiveAggressiveClassification.duplicate()

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos that implement LearningAlgorithm

Modifier and Type	Class and Description
class	PegasosLearningAlgorithm It implements the Primal Estimated sub-GrAdient SOlver (PEGASOS) for SVM.

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron that implement LearningAlgorithm

Modifier and Type	Class and Description
class	KernelizedPerceptron The perceptron learning algorithm algorithm for classification tasks (Kernel machine version).
class	LinearPerceptron The perceptron learning algorithm algorithm for classification tasks (linear version).
class	Perceptron The perceptron learning algorithm algorithm for classification tasks.

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.classification.scw

Classes in it.uniroma2.sag.kelp.learningalgorithm.classification.scw that implement LearningAlgorithm

Modifier and Type	Class and Description
class	SoftConfidenceWeightedClassification Implements Exact Soft Confidence-Weighted (SCW) algorithms, an on-line learning algorithm for binary classification.

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.regression

Subinterfaces of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.regression

Modifier and Type	Interface and Description
interface	RegressionLearningAlgorithm It is a learning algorithm that learn how to solve a generic regression task

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear

Classes in it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear that implement LearningAlgorithm

Modifier and Type	Class and Description
class	LibLinearRegression This class implements linear SVM regression trained using a coordinate descent algorithm [Fan et al, 2008].

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm

Classes in it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm that implement LearningAlgorithm

Modifier and Type	Class and Description
class	EpsilonSvmRegression It implements the \(\epsilon\)-SVR learning algorithm discussed in [CC Chang & CJ Lin, 2011].

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive

Classes in it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive that implement LearningAlgorithm

Modifier and Type	Class and Description
class	KernelizedPassiveAggressiveRegression Online Passive-Aggressive Learning Algorithm for regression tasks (kernel machine version).
class	LinearPassiveAggressiveRegression Online Passive-Aggressive Learning Algorithm for regression tasks (linear version).
class	PassiveAggressiveRegression Online Passive-Aggressive Learning Algorithm for regression tasks.

Uses of LearningAlgorithm in it.uniroma2.sag.kelp.utils

Methods in it.uniroma2.sag.kelp.utils with parameters of type LearningAlgorithm

Modifier and Type	Method and Description
static <T extends Evaluator> List<T>	ExperimentUtils.nFoldCrossValidation(int nFold, LearningAlgorithm algorithm, SimpleDataset allData, T evaluator) Performs a n-fold cross validation