.TH "mlpack::svd::RegularizedSVDFunction" 3 "Tue Sep 9 2014" "Version 1.0.10" "MLPACK" \" -*- nroff -*-
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.SH NAME
mlpack::svd::RegularizedSVDFunction \- 
.SH SYNOPSIS
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.PP
.SS "Public Member Functions"

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.RI "\fBRegularizedSVDFunction\fP (const arma::mat &\fBdata\fP, const size_t \fBrank\fP, const double \fBlambda\fP)"
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.RI "\fIConstructor for \fBRegularizedSVDFunction\fP class\&. \fP"
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.RI "const arma::mat & \fBDataset\fP () const "
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.RI "\fIReturn the dataset passed into the constructor\&. \fP"
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.RI "double \fBEvaluate\fP (const arma::mat &parameters) const "
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.RI "\fIEvaluates the cost function over all examples in the data\&. \fP"
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.RI "double \fBEvaluate\fP (const arma::mat &parameters, const size_t i) const "
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.RI "\fIEvaluates the cost function for one training example\&. \fP"
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.RI "const arma::mat & \fBGetInitialPoint\fP () const "
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.RI "\fIReturn the initial point for the optimization\&. \fP"
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.RI "void \fBGradient\fP (const arma::mat &parameters, arma::mat &gradient) const "
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.RI "\fIEvaluates the full gradient of the cost function over all the training examples\&. \fP"
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.RI "double \fBLambda\fP () const "
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.RI "\fIReturn the regularization parameters\&. \fP"
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.RI "size_t \fBNumFunctions\fP () const "
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.RI "\fIReturn the number of training examples\&. Useful for SGD optimizer\&. \fP"
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.RI "size_t \fBNumItems\fP () const "
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.RI "\fIReturn the number of items in the data\&. \fP"
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.RI "size_t \fBNumUsers\fP () const "
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.RI "\fIReturn the number of users in the data\&. \fP"
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.RI "size_t \fBRank\fP () const "
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.RI "\fIReturn the rank used for the factorization\&. \fP"
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.SS "Private Attributes"

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.RI "const arma::mat & \fBdata\fP"
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.RI "\fIRating data\&. \fP"
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.RI "arma::mat \fBinitialPoint\fP"
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.RI "\fIInitial parameter point\&. \fP"
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.RI "double \fBlambda\fP"
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.RI "\fIRegularization parameter for the optimization\&. \fP"
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.RI "size_t \fBnumItems\fP"
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.RI "\fINumber of items in the given dataset\&. \fP"
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.RI "size_t \fBnumUsers\fP"
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.RI "\fINumber of users in the given dataset\&. \fP"
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.RI "size_t \fBrank\fP"
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.RI "\fIRank used for matrix factorization\&. \fP"
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.SH "Detailed Description"
.PP 
Definition at line 32 of file regularized_svd_function\&.hpp\&.
.SH "Constructor & Destructor Documentation"
.PP 
.SS "mlpack::svd::RegularizedSVDFunction::RegularizedSVDFunction (const arma::mat &data, const size_trank, const doublelambda)"

.PP
Constructor for \fBRegularizedSVDFunction\fP class\&. The constructor calculates the number of users and items in the passed data\&. It also randomly initializes the parameter values\&.
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\fBParameters:\fP
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\fIdata\fP Dataset for which SVD is calculated\&. 
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\fIrank\fP Rank used for matrix factorization\&. 
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\fIlambda\fP Regularization parameter used for optimization\&. 
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.SH "Member Function Documentation"
.PP 
.SS "const arma::mat& mlpack::svd::RegularizedSVDFunction::Dataset () const\fC [inline]\fP"

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Return the dataset passed into the constructor\&. 
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Definition at line 80 of file regularized_svd_function\&.hpp\&.
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References data\&.
.SS "double mlpack::svd::RegularizedSVDFunction::Evaluate (const arma::mat &parameters) const"

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Evaluates the cost function over all examples in the data\&. 
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\fBParameters:\fP
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\fIparameters\fP Parameters(user/item matrices) of the decomposition\&. 
.RE
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.SS "double mlpack::svd::RegularizedSVDFunction::Evaluate (const arma::mat &parameters, const size_ti) const"

.PP
Evaluates the cost function for one training example\&. Useful for the SGD optimizer abstraction which uses one training example at a time\&.
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\fBParameters:\fP
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\fIparameters\fP Parameters(user/item matrices) of the decomposition\&. 
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\fIi\fP Index of the training example to be used\&. 
.RE
.PP

.SS "const arma::mat& mlpack::svd::RegularizedSVDFunction::GetInitialPoint () const\fC [inline]\fP"

.PP
Return the initial point for the optimization\&. 
.PP
Definition at line 77 of file regularized_svd_function\&.hpp\&.
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References initialPoint\&.
.SS "void mlpack::svd::RegularizedSVDFunction::Gradient (const arma::mat &parameters, arma::mat &gradient) const"

.PP
Evaluates the full gradient of the cost function over all the training examples\&. 
.PP
\fBParameters:\fP
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\fIparameters\fP Parameters(user/item matrices) of the decomposition\&. 
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\fIgradient\fP Calculated gradient for the parameters\&. 
.RE
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.SS "double mlpack::svd::RegularizedSVDFunction::Lambda () const\fC [inline]\fP"

.PP
Return the regularization parameters\&. 
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Definition at line 92 of file regularized_svd_function\&.hpp\&.
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References lambda\&.
.SS "size_t mlpack::svd::RegularizedSVDFunction::NumFunctions () const\fC [inline]\fP"

.PP
Return the number of training examples\&. Useful for SGD optimizer\&. 
.PP
Definition at line 83 of file regularized_svd_function\&.hpp\&.
.SS "size_t mlpack::svd::RegularizedSVDFunction::NumItems () const\fC [inline]\fP"

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Return the number of items in the data\&. 
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Definition at line 89 of file regularized_svd_function\&.hpp\&.
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References numItems\&.
.SS "size_t mlpack::svd::RegularizedSVDFunction::NumUsers () const\fC [inline]\fP"

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Return the number of users in the data\&. 
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Definition at line 86 of file regularized_svd_function\&.hpp\&.
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References numUsers\&.
.SS "size_t mlpack::svd::RegularizedSVDFunction::Rank () const\fC [inline]\fP"

.PP
Return the rank used for the factorization\&. 
.PP
Definition at line 95 of file regularized_svd_function\&.hpp\&.
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References rank\&.
.SH "Member Data Documentation"
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.SS "const arma::mat& mlpack::svd::RegularizedSVDFunction::data\fC [private]\fP"

.PP
Rating data\&. 
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Definition at line 99 of file regularized_svd_function\&.hpp\&.
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Referenced by Dataset()\&.
.SS "arma::mat mlpack::svd::RegularizedSVDFunction::initialPoint\fC [private]\fP"

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Initial parameter point\&. 
.PP
Definition at line 101 of file regularized_svd_function\&.hpp\&.
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Referenced by GetInitialPoint()\&.
.SS "double mlpack::svd::RegularizedSVDFunction::lambda\fC [private]\fP"

.PP
Regularization parameter for the optimization\&. 
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Definition at line 105 of file regularized_svd_function\&.hpp\&.
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Referenced by Lambda()\&.
.SS "size_t mlpack::svd::RegularizedSVDFunction::numItems\fC [private]\fP"

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Number of items in the given dataset\&. 
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Definition at line 109 of file regularized_svd_function\&.hpp\&.
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Referenced by NumItems()\&.
.SS "size_t mlpack::svd::RegularizedSVDFunction::numUsers\fC [private]\fP"

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Number of users in the given dataset\&. 
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Definition at line 107 of file regularized_svd_function\&.hpp\&.
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Referenced by NumUsers()\&.
.SS "size_t mlpack::svd::RegularizedSVDFunction::rank\fC [private]\fP"

.PP
Rank used for matrix factorization\&. 
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Definition at line 103 of file regularized_svd_function\&.hpp\&.
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Referenced by Rank()\&.

.SH "Author"
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