C# Class Accord.MachineLearning.Bootstrap

Méthodes publiques

Méthode	Description
Bootstrap ( int size, int subsamples ) : System	Creates a new Bootstrap estimation algorithm.
Bootstrap ( int size, int subsamples, int subsampleSize ) : System	Creates a new Bootstrap estimation algorithm.
Compute ( ) : BootstrapResult	Computes the cross validation algorithm.
CreatePartitions ( int index, int &trainingSet, int &validationSet ) : void	Gets the indices for the training and validation sets for the specified validation fold index.
GetPartitionSize ( int index, int &trainingCount, int &validationCount ) : void	Gets the number of instances in training and validation sets for the specified validation fold index.
Samplings ( int size, int resamplings, int subsampleSize ) : int[][]	Draws the bootstrap samples from the population.

Creates a new Bootstrap estimation algorithm.

public Bootstrap ( int size, int subsamples ) : System
size	int	The size of the complete dataset.
subsamples	int	The number B of bootstrap resamplings to perform.
Résultat	System

Creates a new Bootstrap estimation algorithm.

public Bootstrap ( int size, int subsamples, int subsampleSize ) : System
size	int	The size of the complete dataset.
subsamples	int	The number B of bootstrap resamplings to perform.
subsampleSize	int	The number of samples in each subsample. Default /// is to use the total number of samples in the population dataset.
Résultat	System

Computes the cross validation algorithm.

public Compute ( ) : BootstrapResult
Résultat	BootstrapResult

Gets the indices for the training and validation sets for the specified validation fold index.

public CreatePartitions ( int index, int &trainingSet, int &validationSet ) : void
index	int	The index of the validation fold.
trainingSet	int	The indices for the observations in the training set.
validationSet	int	The indices for the observations in the validation set.
Résultat	void

Gets the number of instances in training and validation sets for the specified validation fold index.

public GetPartitionSize ( int index, int &trainingCount, int &validationCount ) : void
index	int	The index of the bootstrap sample.
trainingCount	int	The number of instances in the training set.
validationCount	int	The number of instances in the validation set.
Résultat	void

Draws the bootstrap samples from the population.

public static Samplings ( int size, int resamplings, int subsampleSize ) : int[][]
size	int	The size of the samples to be drawn.
resamplings	int	The number of samples to drawn.
subsampleSize	int	The size of the samples to be drawn.
Résultat	int[][]