MetaInfoExtractor is a tool for extracting meta information about a given machine learning algorithm. More...
Public Types | |
| using | PredictionsType = typename Select< TF1, TF2, TF3, TF4, TF5 >::Type::PredictionsType |
| The type of predictions used in MLAlgorithm. More... | |
| using | WeightsType = typename Select< WTF1, WTF2, WTF3, WTF4, WTF5 >::Type::WeightsType |
| The type of weights used in MLAlgorithm. More... | |
Static Public Attributes | |
| static const bool | IsSupported = !std::is_same<PredictionsType, void*>::value |
| An indication whether PredictionsType has been identified (i.e. More... | |
| static const bool | SupportsWeights = !std::is_same<WeightsType, void*>::value |
| An indication whether MLAlgorithm supports weighted learning. More... | |
| static const bool | TakesDatasetInfo = Selects<TF5>::value |
| An indication whether MLAlgorithm takes a data::DatasetInfo parameter. More... | |
| static const bool | TakesNumClasses = Selects<TF4, TF5>::value |
| An indication whether MLAlgorithm takes the numClasses (size_t) parameter. More... | |
Detailed Description
template<typename MLAlgorithm, typename MT = arma::mat, typename PT = arma::Row<size_t>, typename WT = arma::rowvec>
class mlpack::cv::MetaInfoExtractor< MLAlgorithm, MT, PT, WT >
MetaInfoExtractor is a tool for extracting meta information about a given machine learning algorithm.
It can be used to automatically extract the type of predictions and weights (if weighted learning is supported), whether the machine learning algorithm takes a DatasetInfo parameter or a numClasses parameter.
The following assumptions are made about the machine learning algorithm.
- All needed information can be extracted from signatures of Train methods.
- The machine learning algorithm contains either only non-templated Train methods or only templated ones.
- Train methods that can be used for extraction of needed information should be distinguishable by a number of arguments (for more information read discussion in https://github.com/mlpack/mlpack/issues/929).
- If weighted learning is supported, passing weights is an option rather than a requirement.
- Template Parameters
-
MLAlgorithm A machine learning algorithm to investigate. MT The type of data. PT The type of predictions (should be passed when the predictions type is a template parameter in Train methods of MLAlgorithm). WT The type of weights (should be passed when weighted learning is supported, and the weights type is a template parameter in Train methods of MLAlgorithm).
Definition at line 272 of file meta_info_extractor.hpp.
Member Typedef Documentation
◆ PredictionsType
The type of predictions used in MLAlgorithm.
It is equal to void* if the extraction fails.
Definition at line 319 of file meta_info_extractor.hpp.
◆ WeightsType
The type of weights used in MLAlgorithm.
It is equal to void* if the extraction fails.
Definition at line 326 of file meta_info_extractor.hpp.
Member Data Documentation
◆ IsSupported
|
static |
An indication whether PredictionsType has been identified (i.e.
MLAlgorithm is supported by MetaInfoExtractor).
Definition at line 332 of file meta_info_extractor.hpp.
◆ SupportsWeights
|
static |
An indication whether MLAlgorithm supports weighted learning.
Definition at line 337 of file meta_info_extractor.hpp.
◆ TakesDatasetInfo
|
static |
An indication whether MLAlgorithm takes a data::DatasetInfo parameter.
Definition at line 342 of file meta_info_extractor.hpp.
◆ TakesNumClasses
An indication whether MLAlgorithm takes the numClasses (size_t) parameter.
Definition at line 347 of file meta_info_extractor.hpp.
The documentation for this class was generated from the following file:
- /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/core/cv/meta_info_extractor.hpp