Ryan BirminghamandRyan Curtin
8f87dbb548
thanks @rcurtin Co-authored-by: Ryan Curtin <ryan@ratml.org>
43 lines
1.4 KiB
C++
43 lines
1.4 KiB
C++
/*! @page elem The ElemType policy in mlpack
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@section elem_overview Overview
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\b mlpack algorithms should be as generic as possible. Often this means
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allowing arbitrary metrics or kernels to be used, but this also means allowing
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any type of data point to be used. This means that \b mlpack classes should
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support \c float, \c double, and other observation types. Some algorithms
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support this through the use of a \c MatType template parameter; others will
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have their own template parameter, \c ElemType.
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The \c ElemType template parameter can take any value that can be used by
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Armadillo (or, specifically, classes like \c arma::Mat<> and others); this
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encompasses the types
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- \c double
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- \c float
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- \c int
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- \c unsigned int
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- \c std::complex<double>
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- \c std::complex<float>
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and other primitive numeric types. Note that Armadillo does not support some
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integer types for functionality such as matrix decompositions or other more
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advanced linear algebra. This means that when these integer types are used,
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some algorithms may fail with Armadillo error messages indicating that those
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types cannot be used.
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@section A note for developers
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If the class has a \c MatType template parameter, \c ElemType can be easily
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defined as below:
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@code
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typedef typename MatType::elem_type ElemType;
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@endcode
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and otherwise a template parameter with the name \c ElemType can be used. It is
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generally a good idea to expose the element type somehow for use by other
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classes.
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*/
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