SHOGUN  6.0.0
rowwise_mean< Backend::EIGEN3, Matrix > Struct Template Reference

## Detailed Description

### template<class Matrix> struct shogun::linalg::implementation::rowwise_mean< Backend::EIGEN3, Matrix >

Specialization of generic mean which works with SGMatrix and uses Eigen3 as backend for computing rowwise mean.

Definition at line 207 of file MeanEigen3.h.

## Public Types

typedef Matrix::Scalar T

typedef int2float< T >::floatType ReturnDataType

typedef Eigen::Matrix< T,
Eigen::Dynamic, Eigen::Dynamic >
MatrixXt

## Static Public Member Functions

static SGVector< ReturnDataTypecompute (SGMatrix< T > m, bool no_diag)

static void compute (SGMatrix< T > mat, SGVector< ReturnDataType > result, bool no_diag)

## Member Typedef Documentation

 typedef Eigen::Matrix MatrixXt

Eigen matrix type

Definition at line 216 of file MeanEigen3.h.

 typedef int2float::floatType ReturnDataType

int2float type

Definition at line 213 of file MeanEigen3.h.

 typedef Matrix::Scalar T

Scalar type

Definition at line 210 of file MeanEigen3.h.

## Member Function Documentation

 static SGVector compute ( SGMatrix< T > m, bool no_diag )
static

Method that computes the rowwise mean of SGMatrix using Eigen3

Parameters
 m the matrix whose rowwise mean has to be computed no_diag if true, diagonal entries are excluded from the mean
Returns
the rowwise mean computed as $$\1/N \sum_{j=1}^N m_{i,j}$$

Definition at line 225 of file MeanEigen3.h.

 static void compute ( SGMatrix< T > mat, SGVector< ReturnDataType > result, bool no_diag )
static

Method that computes the rowwise mean of SGMatrix using Eigen3

Parameters
 mat the matrix whose rowwise mean has to be computed no_diag if true, diagonal entries are excluded from the mean result Pre-allocated vector for the result of the computation

Definition at line 239 of file MeanEigen3.h.

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

SHOGUN Machine Learning Toolbox - Documentation