Uses of Interface
it.uniroma2.sag.kelp.data.dataset.Dataset

Packages that use Dataset

Package	Description
it.uniroma2.sag.kelp.data.dataset
it.uniroma2.sag.kelp.learningalgorithm
it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm
it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear
it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear.solver
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.clustering
it.uniroma2.sag.kelp.learningalgorithm.clustering.kernelbasedkmeans
it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm
it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive

Uses of Dataset in it.uniroma2.sag.kelp.data.dataset

Classes in it.uniroma2.sag.kelp.data.dataset that implement Dataset

Modifier and Type	Class and Description
class	SimpleDataset A SimpleDataset that represent a whole dataset in memory.

Methods in it.uniroma2.sag.kelp.data.dataset that return Dataset

Modifier and Type	Method and Description
static Dataset	SimpleDataset.extractExamplesOfClasses(Dataset dataset, List<Label> labels) This method extracts examples of given labels from dataset
Dataset	Dataset.getShuffledDataset()
Dataset[]	SimpleDataset.nFolding(int n) Returns n datasets.
Dataset[]	SimpleDataset.nFoldingClassDistributionInvariant(int n) Returns n datasets.
Dataset[]	SimpleDataset.split(float percentage) Returns two datasets created by splitting this dataset accordingly to percentage.
Dataset[]	SimpleDataset.splitClassDistributionInvariant(float percentage) Returns two datasets created by splitting this dataset accordingly to percentage.

Methods in it.uniroma2.sag.kelp.data.dataset with parameters of type Dataset

Modifier and Type	Method and Description
void	SimpleDataset.addExamples(Dataset datasetToBeAdded) Add all the examples contained in datasetToBeAdded
static Dataset	SimpleDataset.extractExamplesOfClasses(Dataset dataset, List<Label> labels) This method extracts examples of given labels from dataset

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

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

Modifier and Type	Method and Description
void	LearningAlgorithm.learn(Dataset dataset) It starts the training process exploiting the provided dataset
void	PassiveAggressive.learn(Dataset dataset)
void	MultiEpochLearning.learn(Dataset dataset)

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

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

Modifier and Type	Method and Description
void	BudgetedLearningAlgorithm.learn(Dataset dataset)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear with parameters of type Dataset

Modifier and Type	Method and Description
void	LibLinearLearningAlgorithm.learn(Dataset dataset)

Uses of Dataset in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear.solver

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear.solver with parameters of type Dataset

Constructor and Description
Problem(Dataset dataset, String reprentationName, Label label)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm with parameters of type Dataset

Modifier and Type	Method and Description
void	OneClassSvmClassification.learn(Dataset trainingSet)
void	BinaryNuSvmClassification.learn(Dataset trainingSet)
void	BinaryCSvmClassification.learn(Dataset trainingSet)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver with parameters of type Dataset

Modifier and Type	Method and Description
protected float[]	LibCSvmSolver.getCSvmAlpha(Dataset trainingSet) Get the initial weight for the future Support Vectors
SvmSolution	LibSvmSolver.solve(int l_, Dataset dataset, float[] p_, int[] y_, float[] initial_alpha) It solves the SMO algorithm in [CC Chang & CJ Lin, 2011] min 0.5(\alpha^T Q \alpha) + p^T \alpha y^T \alpha = \delta y_i = +1 or -1 0 <= alpha_i <= Cp for y_i = 1 0 <= alpha_i <= Cn for y_i = -1 Given: Q, p, y, Cp, Cn, and an initial feasible point \alpha l is the size of vectors and matrices eps is the stopping tolerance solution will be put in \alpha, objective value will be put in obj

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

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

Modifier and Type	Method and Description
void	OneVsOneLearning.learn(Dataset dataset) This method will cause the meta-learning algorithm to learn N*(N-1)/2 classifiers, where N is the number of classes in the dataset.
void	OneVsAllLearning.learn(Dataset dataset) This method will cause the meta-learning algorithm to learn N classifiers, where N is the number of classes in the dataset.

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive with parameters of type Dataset

Modifier and Type	Method and Description
void	PassiveAggressiveClassification.learn(Dataset dataset)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos with parameters of type Dataset

Modifier and Type	Method and Description
void	PegasosLearningAlgorithm.learn(Dataset dataset)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron with parameters of type Dataset

Modifier and Type	Method and Description
void	Perceptron.learn(Dataset dataset)

Uses of Dataset in it.uniroma2.sag.kelp.learningalgorithm.clustering

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

Modifier and Type	Method and Description
List<Cluster>	ClusteringAlgorithm.cluster(Dataset dataset) It starts the clustering process exploiting the provided dataset

Uses of Dataset in it.uniroma2.sag.kelp.learningalgorithm.clustering.kernelbasedkmeans

Methods in it.uniroma2.sag.kelp.learningalgorithm.clustering.kernelbasedkmeans with parameters of type Dataset

Modifier and Type	Method and Description
List<Cluster>	KernelBasedKMeansEngine.cluster(Dataset dataset)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm with parameters of type Dataset

Modifier and Type	Method and Description
void	EpsilonSvmRegression.learn(Dataset dataset)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive with parameters of type Dataset

Modifier and Type	Method and Description
void	PassiveAggressiveRegression.learn(Dataset dataset)