GaussianInitialization Class Reference

This class is used to initialize weigth matrix with a gaussian. More...

Public Member Functions

 GaussianInitialization (const double mean=0, const double variance=1)
 Initialize the gaussian with the given mean and variance. More...

 
template
<
typename
eT
>
void Initialize (arma::Mat< eT > &W, const size_t rows, const size_t cols)
 Initialize the elements weight matrix using a Gaussian Distribution. More...

 
template
<
typename
eT
>
void Initialize (arma::Cube< eT > &W, const size_t rows, const size_t cols, const size_t slices)
 Initialize randomly the elements of the specified weight 3rd order tensor. More...

 

Detailed Description

This class is used to initialize weigth matrix with a gaussian.

Definition at line 28 of file gaussian_init.hpp.

Constructor & Destructor Documentation

◆ GaussianInitialization()

GaussianInitialization ( const double  mean = 0,
const double  variance = 1 
)
inline

Initialize the gaussian with the given mean and variance.

Parameters
meanMean of the gaussian.
varianceVariance of the gaussian.

Definition at line 37 of file gaussian_init.hpp.

Member Function Documentation

◆ Initialize() [1/2]

void Initialize ( arma::Mat< eT > &  W,
const size_t  rows,
const size_t  cols 
)
inline

Initialize the elements weight matrix using a Gaussian Distribution.

Parameters
WWeight matrix to initialize.
rowsNumber of rows.
colsNumber of columns.

Definition at line 51 of file gaussian_init.hpp.

References mlpack::math::RandNormal().

Referenced by GlorotInitializationType< Uniform >::Initialize().

◆ Initialize() [2/2]

void Initialize ( arma::Cube< eT > &  W,
const size_t  rows,
const size_t  cols,
const size_t  slices 
)
inline

Initialize randomly the elements of the specified weight 3rd order tensor.

Parameters
WWeight matrix to initialize.
rowsNumber of rows.
colsNumber of columns.
sliceNumbers of slices.

Definition at line 71 of file gaussian_init.hpp.


The documentation for this class was generated from the following file:
  • /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.2.1/src/mlpack/methods/ann/init_rules/gaussian_init.hpp