This class implements SVD batch learning with momentum. More...

Public Member Functions
	SVDBatchLearning (double u=0.0002, double kw=0, double kh=0, double momentum=0.9)
	SVD Batch learning constructor. More...

template < typename MatType >
void	HUpdate (const MatType &V, const arma::mat &W, arma::mat &H)
	The update rule for the encoding matrix H. More...

template < typename MatType >
void	Initialize (const MatType &dataset, const size_t rank)
	Initialize parameters before factorization. More...

template < typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the SVDBatch object. More...

template < typename MatType >
void	WUpdate (const MatType &V, arma::mat &W, const arma::mat &H)
	The update rule for the basis matrix W. More...

Detailed Description

This class implements SVD batch learning with momentum.

This procedure is described in the following paper:

@techreport{ma2008guide,
  title={A Guide to Singular Value Decomposition for Collaborative
      Filtering},
  author={Ma, Chih-Chao},
  year={2008},
  institution={Department of Computer Science, National Taiwan University}
}

This class implements 'Algorithm 4' as given in the paper.

The factorizer decomposes the matrix V into two matrices W and H such that sum of sum of squared error between V and W * H is minimum. This optimization is performed with gradient descent. To make gradient descent faster, momentum is added.

Definition at line 41 of file svd_batch_learning.hpp.

Constructor & Destructor Documentation

◆ SVDBatchLearning()

SVDBatchLearning	(	double	u = `0.0002`,
		double	kw = `0`,
		double	kh = `0`,
		double	momentum = `0.9`
	)

inline

SVD Batch learning constructor.

Parameters

u	step value used in batch learning
kw	regularization constant for W matrix
kh	regularization constant for H matrix
momentum	momentum applied to batch learning process

Definition at line 52 of file svd_batch_learning.hpp.

Member Function Documentation

◆ HUpdate()

void HUpdate	(	const MatType &	V,
		const arma::mat &	W,
		arma::mat &	H
	)

inline

The update rule for the encoding matrix H.

The function takes in all the matrices and only changes the value of the H matrix.

Parameters

V	Input matrix to be factorized.
W	Basis matrix.
H	Encoding matrix to be updated.

Definition at line 133 of file svd_batch_learning.hpp.

◆ Initialize()

void Initialize	(	const MatType &	dataset,
		const size_t	rank
	)

inline

Initialize parameters before factorization.

This function must be called before a new factorization. This resets the internally-held momentum.

Parameters

dataset	Input matrix to be factorized.
rank	rank of factorization

Definition at line 69 of file svd_batch_learning.hpp.

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

inline

Serialize the SVDBatch object.

Definition at line 169 of file svd_batch_learning.hpp.

◆ WUpdate()

void WUpdate	(	const MatType &	V,
		arma::mat &	W,
		const arma::mat &	H
	)

inline

The update rule for the basis matrix W.

The function takes in all the matrices and only changes the value of the W matrix.

Parameters

V	Input matrix to be factorized.
W	Basis matrix to be updated.
H	Encoding matrix.

Definition at line 88 of file svd_batch_learning.hpp.

The documentation for this class was generated from the following file:

/home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/amf/update_rules/svd_batch_learning.hpp

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ SVDBatchLearning()

Member Function Documentation

◆ HUpdate()

◆ Initialize()

◆ serialize()

◆ WUpdate()