Superclass of supervised learning algorithms. More...
#include <shark/Algorithms/Trainers/AbstractTrainer.h>
Inheritance diagram for shark::AbstractTrainer< Model, LabelTypeT >:
Public Types | |
| typedef Model | ModelType |
| typedef ModelType::InputType | InputType |
| typedef LabelTypeT | LabelType |
| typedef LabeledData< InputType, LabelType > | DatasetType |
Public Member Functions | |
| virtual void | train (ModelType &model, DatasetType const &dataset)=0 |
| Core of the Trainer interface. More... | |
| Public Member Functions inherited from shark::INameable | |
| virtual | ~INameable () |
| virtual std::string | name () const |
| returns the name of the object More... | |
| Public Member Functions inherited from shark::ISerializable | |
| virtual | ~ISerializable () |
| Virtual d'tor. More... | |
| virtual void | read (InArchive &archive) |
| Read the component from the supplied archive. More... | |
| virtual void | write (OutArchive &archive) const |
| Write the component to the supplied archive. More... | |
| void | load (InArchive &archive, unsigned int version) |
| Versioned loading of components, calls read(...). More... | |
| void | save (OutArchive &archive, unsigned int version) const |
| Versioned storing of components, calls write(...). More... | |
| BOOST_SERIALIZATION_SPLIT_MEMBER () | |
Detailed Description
template<class Model, class LabelTypeT = typename Model::OutputType>
class shark::AbstractTrainer< Model, LabelTypeT >
Superclass of supervised learning algorithms.
- AbstractTrainer is the super class of all trainers, i.e., procedures for training or learning model parameters. It provides a single virtual function to train the model.
- Note: Most learning algorithms of this type operate on a special model type, such as a linear model, a kernel expansion, etc. Thus, these algorithms should provide a specialized train method accepting only this model type. The virtual train method should be overriden with a method that checks the type of the model and calls the specialized train method.
Definition at line 64 of file AbstractTrainer.h.
Member Typedef Documentation
§ DatasetType
| typedef LabeledData<InputType, LabelType> shark::AbstractTrainer< Model, LabelTypeT >::DatasetType |
Definition at line 70 of file AbstractTrainer.h.
§ InputType
| typedef ModelType::InputType shark::AbstractTrainer< Model, LabelTypeT >::InputType |
Definition at line 68 of file AbstractTrainer.h.
§ LabelType
| typedef LabelTypeT shark::AbstractTrainer< Model, LabelTypeT >::LabelType |
Definition at line 69 of file AbstractTrainer.h.
§ ModelType
| typedef Model shark::AbstractTrainer< Model, LabelTypeT >::ModelType |
Definition at line 67 of file AbstractTrainer.h.
Member Function Documentation
§ train()
|
pure virtual |
Core of the Trainer interface.
Implemented in shark::AbstractWeightedTrainer< Model, LabelTypeT >, shark::AbstractWeightedTrainer< LinearClassifier<>, unsigned int >, and shark::AbstractWeightedTrainer< KernelClassifier< InputType > >.
Referenced by shark::LooError< ModelTypeT, LabelType >::eval(), and shark::CrossValidationError< ModelTypeT, LabelTypeT >::eval().
The documentation for this class was generated from the following file:
- include/shark/Algorithms/Trainers/AbstractTrainer.h