mlpack::ann::OivsInitialization< ActivationFunction > Class Template Reference

This class is used to initialize the weight matrix with the oivs method. More...

#include <oivs_init.hpp>

Public Member Functions
	OivsInitialization (const double epsilon=0.1, const int k=5, const double gamma=0.9)
	Initialize the random initialization rule with the given values. More...
template<typename eT >
void	Initialize (arma::Mat< eT > &W, const size_t rows, const size_t cols)
	Initialize the elements of the specified weight matrix with the oivs method. More...
template<typename eT >
void	Initialize (arma::Mat< eT > &W)
	Initialize the elements of the specified weight matrix with the oivs method. More...
template<typename eT >
void	Initialize (arma::Cube< eT > &W, const size_t rows, const size_t cols, const size_t slices)
	Initialize the elements of the specified weight 3rd order tensor with the oivs method. More...
template<typename eT >
void	Initialize (arma::Cube< eT > &W)
	Initialize the elements of the specified weight 3rd order tensor with the oivs method. More...

Detailed Description

template<class ActivationFunction = LogisticFunction>
class mlpack::ann::OivsInitialization< ActivationFunction >

This class is used to initialize the weight matrix with the oivs method.

The method is based on the equations representing the characteristics of the information transformation mechanism of a node. The method is defined by

\begin{eqnarray*} b &=& |F^{-1}(1 - \epsilon) - f^{-1}(\epsilon)| \\ \hat{w} &=& \frac{b}{k \cdot n} \\ \gamma &\le& a_i \le \gamma \\ w_i &=& \hat{w} \cdot \sqrt{a_i + 1} \end{eqnarray*}

Where f is the transfer function epsilon, k custom parameters, n the number of neurons in the outgoing layer and gamma a parameter that defines the random interval.

Template Parameters

ActivationFunction

The activation function used for the oivs method.

Constructor & Destructor Documentation

OivsInitialization()

template<class ActivationFunction = LogisticFunction>

mlpack::ann::OivsInitialization< ActivationFunction >::OivsInitialization ( const double  epsilon = 0.1, const int  k = 5, const double  gamma = 0.9  )

inline

Initialize the random initialization rule with the given values.

Parameters

epsilon	Parameter to control the activation region.
k	Parameter to control the activation region width.
gamma	Parameter to define the uniform random range.

Member Function Documentation

Initialize() [1/4]

template<class ActivationFunction = LogisticFunction>

template<typename eT >

void mlpack::ann::OivsInitialization< ActivationFunction >::Initialize ( arma::Mat< eT > &  W, const size_t  rows, const size_t  cols  )

inline

Initialize the elements of the specified weight matrix with the oivs method.

Parameters

W	Weight matrix to initialize.
rows	Number of rows.
cols	Number of columns.

Initialize() [2/4]

template<class ActivationFunction = LogisticFunction>

template<typename eT >

void mlpack::ann::OivsInitialization< ActivationFunction >::Initialize ( arma::Mat< eT > &  W )

inline

Initialize the elements of the specified weight matrix with the oivs method.

Parameters

W	Weight matrix to initialize.

Initialize() [3/4]

template<class ActivationFunction = LogisticFunction>

template<typename eT >

void mlpack::ann::OivsInitialization< ActivationFunction >::Initialize ( arma::Cube< eT > &  W, const size_t  rows, const size_t  cols, const size_t  slices  )

inline

Initialize the elements of the specified weight 3rd order tensor with the oivs method.

Parameters

W	3rd order tensor to initialize.
rows	Number of rows.
cols	Number of columns.
slices	Number of slices.

Initialize() [4/4]

template<class ActivationFunction = LogisticFunction>

template<typename eT >

void mlpack::ann::OivsInitialization< ActivationFunction >::Initialize ( arma::Cube< eT > &  W )

inline

Initialize the elements of the specified weight 3rd order tensor with the oivs method.

Parameters

W	3rd order tensor to initialize.

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

• src/mlpack/methods/ann/init_rules/oivs_init.hpp