coco
164 lines
5.7 KiB
C++
164 lines
5.7 KiB
C++
// Copyright (C) 2010 Davis E. King (davis@dlib.net)
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// License: Boost Software License See LICENSE.txt for the full license.
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#undef DLIB_ONE_VS_ALL_TRAiNER_ABSTRACT_Hh_
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#ifdef DLIB_ONE_VS_ALL_TRAiNER_ABSTRACT_Hh_
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#include "one_vs_all_decision_function_abstract.h"
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#include <vector>
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#include "../any/any_trainer_abstract.h"
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namespace dlib
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{
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// ----------------------------------------------------------------------------------------
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template <
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typename any_trainer,
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typename label_type_ = double
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>
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class one_vs_all_trainer
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{
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/*!
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REQUIREMENTS ON any_trainer
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must be an instantiation of the dlib::any_trainer template.
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REQUIREMENTS ON label_type_
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label_type_ must be default constructable, copyable, and comparable using
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operator < and ==. It must also be possible to write it to an std::ostream
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using operator<<.
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WHAT THIS OBJECT REPRESENTS
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This object is a tool for turning a bunch of binary classifiers into a
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multiclass classifier. It does this by training the binary classifiers
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in a one vs. all fashion. That is, if you have N possible classes then
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it trains N binary classifiers which are then used to vote on the identity
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of a test sample.
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This object works with any kind of binary classification trainer object
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capable of being assigned to an any_trainer object. (e.g. the svm_nu_trainer)
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!*/
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public:
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typedef label_type_ label_type;
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typedef typename any_trainer::sample_type sample_type;
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typedef typename any_trainer::scalar_type scalar_type;
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typedef typename any_trainer::mem_manager_type mem_manager_type;
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typedef one_vs_all_decision_function<one_vs_all_trainer> trained_function_type;
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one_vs_all_trainer (
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);
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/*!
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ensures
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- This object is properly initialized.
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- This object will not be verbose unless be_verbose() is called.
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- No binary trainers are associated with *this. I.e. you have to
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call set_trainer() before calling train().
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- #get_num_threads() == 4
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!*/
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void set_trainer (
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const any_trainer& trainer
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);
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/*!
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ensures
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- sets the trainer used for all binary subproblems. Any previous
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calls to set_trainer() are overridden by this function. Even the
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more specific set_trainer(trainer, l) form.
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!*/
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void set_trainer (
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const any_trainer& trainer,
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const label_type& l
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);
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/*!
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ensures
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- Sets the trainer object used to create a binary classifier to
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distinguish l labeled samples from all other samples.
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!*/
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void be_verbose (
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);
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/*!
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ensures
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- This object will print status messages to standard out so that a
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user can observe the progress of the algorithm.
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!*/
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void be_quiet (
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);
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/*!
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ensures
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- this object will not print anything to standard out
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!*/
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void set_num_threads (
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unsigned long num
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);
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/*!
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ensures
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- #get_num_threads() == num
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!*/
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unsigned long get_num_threads (
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) const;
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/*!
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ensures
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- returns the number of threads used during training. You should
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usually set this equal to the number of processing cores on your
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machine.
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!*/
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struct invalid_label : public dlib::error
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{
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/*!
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This is the exception thrown by the train() function below.
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!*/
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label_type l;
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};
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trained_function_type train (
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const std::vector<sample_type>& all_samples,
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const std::vector<label_type>& all_labels
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) const;
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/*!
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requires
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- is_learning_problem(all_samples, all_labels)
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ensures
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- trains a bunch of binary classifiers in a one vs all fashion to solve the given
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multiclass classification problem.
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- returns a one_vs_all_decision_function F with the following properties:
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- F contains all the learned binary classifiers and can be used to predict
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the labels of new samples.
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- if (new_x is a sample predicted to have a label of L) then
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- F(new_x) == L
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- F.get_labels() == select_all_distinct_labels(all_labels)
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- F.number_of_classes() == select_all_distinct_labels(all_labels).size()
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throws
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- invalid_label
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This exception is thrown if there are labels in all_labels which don't have
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any corresponding trainer object. This will never happen if set_trainer(trainer)
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has been called. However, if only the set_trainer(trainer,l) form has been
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used then this exception is thrown if not all labels have been given a trainer.
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invalid_label::l will contain the label which is missing a trainer object.
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Additionally, the exception will contain an informative error message available
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via invalid_label::what().
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!*/
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};
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// ----------------------------------------------------------------------------------------
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}
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#endif // DLIB_ONE_VS_ALL_TRAiNER_ABSTRACT_Hh_
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