The ElemType policy in mlpack

mlpack algorithms should be as generic as possible. Often this means allowing arbitrary metrics or kernels to be used, but this also means allowing any type of data point to be used. This means that mlpack classes should support float, double, and other observation types. Some algorithms support this through the use of a MatType template parameter; others will have their own template parameter, ElemType.

The ElemType template parameter can take any value that can be used by Armadillo (or, specifically, classes like arma::Mat<> and others); this encompasses the types

double
float
int
unsigned int
std::complex<double>
std::complex<float>

and other primitive numeric types. Note that Armadillo does not support some integer types for functionality such as matrix decompositions or other more advanced linear algebra. This means that when these integer types are used, some algorithms may fail with Armadillo error messages indicating that those types cannot be used.

Note: if the class has a MatType template parameter, ElemType can be easily defined as below:

typedef typename MatType::elem_type ElemType;

and otherwise a template parameter with the name ElemType can be used. It is generally a good idea to expose the element type somehow for use by other classes.