SHOGUN  6.0.0
rowwise_mean< backend, Matrix > Struct Template Reference

## Detailed Description

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

Generic class rowwise_mean which provides a static compute method.

Definition at line 117 of file MeanEigen3.h.

## Public Types

typedef Matrix::Scalar T

typedef int2float< T >::floatType ReturnDataType

## 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 int2float::floatType ReturnDataType

int2float type

Definition at line 123 of file MeanEigen3.h.

 typedef Matrix::Scalar T

Scalar type

Definition at line 120 of file MeanEigen3.h.

## Member Function Documentation

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

Method that computes the row wise sum of co-efficients of SGMatrix using Eigen3

Parameters
 m the matrix whose rowwise sum of co-efficients has to be computed no_diag if true, diagonal entries are excluded from the sum
Returns
the rowwise sum of co-efficients computed as $$s_i=\sum_{j}m_{i,j}$$
 static void compute ( SGMatrix< T > mat, SGVector< ReturnDataType > result, bool no_diag )
static

Method that computes the row wise sum of co-efficients of SGMatrix using Eigen3

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

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

SHOGUN Machine Learning Toolbox - Documentation