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

Packages that use MetaLearningAlgorithm

Package	Description
it.uniroma2.sag.kelp.learningalgorithm
it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm
it.uniroma2.sag.kelp.learningalgorithm.classification.hmm
it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification

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

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

Modifier and Type	Class and Description
class	MultiEpochLearning It is a meta learning algorithms for online learning methods.

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

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

Modifier and Type	Class and Description
class	RandomizedBudgetPerceptron It is a variation of the Randomized Budget Perceptron proposed in
class	Stoptron It is a variation of the Stoptron proposed in

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

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

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.

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

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

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.